Exploring risk factors and molecular targets in leukemia patients with COVID-19: a bioinformatics analysis of differential gene expression.

The molecular mechanism of COVID-19's pathogenic effects in leukemia patients is still poorly known. Our study investigated the possible disease mechanism of COVID-19 and its associated risk factors in patients with leukemia utilizing differential gene expression analysis. We also employed network-based approaches to identify molecular targets that could potentially diagnose and treat COVID-19-infected leukemia patients. Our study demonstrated a shared set of 60 genes that are expressed differentially among patients with leukemia and COVID-19. Most of these genes are expressed in blood and bone marrow tissues and are predominantly implicated in the pathogenesis of different hematologic malignancies, increasingly imperiling COVID-19 morbidity and mortality among the affected patients. Additionally, we also found that COVID-19 may influence the expression of several cancer-associated genes in leukemia patients, such as CCR7, LEF1, and 13 candidate cancer-driver genes. Furthermore, our findings reveal that COVID-19 may predispose leukemia patients to altered blood homeostasis, increase the risk of COVID-19-related liver injury, and deteriorate leukemia-associated injury and patient prognosis. Our findings imply that molecular signatures, like transcription factors, proteins such as TOP21, and 25 different microRNAs, may be potential targets for diagnosing and treating COVID-19-infected leukemia patients. Nevertheless, additional experimental studies will contribute to further validating the study's findings.

Blood lead, cadmium and hair mercury concentrations and association with soil, dust and occupational factors in e-waste recycling workers in Bangladesh.

BACKGROUND: Electronic waste (e-waste) recycling activities release toxic metals, which pose substantial hazard to the environment and human health. We evaluated metal concentrations in biological and environmental samples, and examined the associations between biological lead (Pb), cadmium (Cd), and mercury (Hg) with soil and dust metals, and other possible determinants, among populations exposed and non-exposed to e-waste in Bangladesh. METHODS: A total of 199 e-waste workers and 104 non-exposed individuals were recruited. We measured blood Pb (BPb) and Cd (BCd) concentrations and total Hg (THg) from hair samples. Data were collected on occupational, and behavioral factors. We fitted an elastic net regression (ENET) to model the relationship between a set of influencing factors and metals as outcome variables while controlling for potential covariates. RESULTS: The median concentrations of BPb (11.89 µg/dL) and BCd (1.04 µg/L) among exposed workers were higher than those of non-exposed workers (BPb: 3.63 µg/dL and BCd: 0.83 µg/L respectively). A 100 ppm increment in soil Pb level was associated with an increase in ln-Pb (transformed) in blood (ß = 0.002; 95% CI = 0.00, 0.02). Similarly, ln-BCd level increased (ß = 0.02; 95% CI = 0.001, 0.07) with every ppm increase in dust Cd level. The number of years worked in e-waste activities was associated with elevated ln-BPb (ß = 0.01; 95% CI = 0.01, 0.02) and ln-BCd levels (ß = 0.003; 95% CI = 0.00, 0.05). Smoking significantly contributed to elevated levels of ln-BCd (ß = 0.46; 95% CI = 0.43, 0.73). An increment of 100 kg of e-waste handling per week led to an increase in ln-BPb levels (ß = 0.002; 95% CI = 0.00, 0.01), while respondents knowledge about adverse impact on e-waste reduced the ln-BPb level (ß = -0.14; 95% CI = -0.31, -0.03). Fish consumption frequency had a positive association with THg in hair. CONCLUSIONS: Our data show the need for workplace controls to reduce exposure to Pb and Cd with a broader view of exposure source taken.

Correction: An immunoinformatics and extended molecular dynamics approach for designing a polyvalent vaccine against multiple strains of Human T-lymphotropic virus (HTLV).

[This corrects the article DOI: 10.1371/journal.pone.0287416.].

An immunoinformatics and extended molecular dynamics approach for designing a polyvalent vaccine against multiple strains of Human T-lymphotropic virus (HTLV).

Human T-lymphotropic virus (HTLV), a group of retroviruses belonging to the oncovirus family, has long been associated with various inflammatory and immunosuppressive disorders. At present, there is no approved vaccine capable of effectively combating all the highly pathogenic strains of HTLV that makes this group of viruses a potential threat to human health. To combat the devastating impact of any potential future outbreak caused by this virus group, our study employed a reverse vaccinology approach to design a novel polyvalent vaccine targeting the highly virulent subtypes of HTLV. Moreover, we comprehensively analyzed the molecular interactions between the designed vaccine and corresponding Toll-like receptors (TLRs), providing valuable insights for future research on preventing and managing HTLV-related diseases and any possible outbreaks. The vaccine was designed by focusing on the envelope glycoprotein gp62, a crucial protein involved in the infectious process and immune mechanisms of HTLV inside the human body. Epitope mapping identified T cell and B cell epitopes with low binding energies, ensuring their immunogenicity and safety. Linkers and adjuvants were incorporated to enhance the vaccine's stability, antigenicity, and immunogenicity. Initially, two vaccine constructs were formulated, and among them, vaccine construct-2 exhibited superior solubility and structural stability. Molecular docking analyses also revealed strong binding affinity between the vaccine construct-2 and both targeted TLR2 and TLR4. Molecular dynamics simulations demonstrated enhanced stability, compactness, and consistent hydrogen bonding within TLR-vaccine complexes, suggesting a strong binding affinity. The stability of the complexes was further corroborated by contact, free energy, structure, and MM-PBSA analyses. Consequently, our research proposes a vaccine targeting multiple HTLV subtypes, offering valuable insights into the molecular interactions between the vaccine and TLRs. These findings should contribute to developing effective preventive and treatment approaches against HTLV-related diseases and preventing possible outbreaks. However, future research should focus on in-depth validation through experimental studies to confirm the interactions identified in silico and to evaluate the vaccine's efficacy in relevant animal models and, eventually, in clinical trials.

Towards associating negative experiences and recommendations reported by Hajj pilgrims in a mass-scale survey.

The annual Hajj presents diversified negative experiences to millions of pilgrims worldwide. The negative experiences and recommendations to overcome them as per pilgrims' feedback are yet to be analyzed from an aggregated perspective in the literature, which we do in this paper. To do so, first, we perform a large-scale survey (n=988) using our comprehensive questionnaire. Then, we perform both quantitative (e.g., clustering) and qualitative (e.g., thematic) analyses on the survey data. Our quantitative analysis reveals up to seven clusters of negative experiences. Further, going beyond the quantitative analysis, our qualitative analysis reveals 21 types of negative experiences, 20 types of recommendations, and nine themes connecting the negative experiences and recommendations. Accordingly, we reveal associations among the negative experiences and recommendations based on the themes in thematic analysis and present the associations through a tripartite graph. However, we have some limitations in this study, such as fewer female and young participants. In future, we plan to collect more responses from female and young participants and extend our work by analyzing linkages in the tripartite graph by augmenting the edges within the graph with appropriate weights. Overall, the findings of this study are expected to facilitate the prioritization of tasks for the management personnel in charge of the Hajj pilgrimage.

Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework.

Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

A review on structural, non-structural, and accessory proteins of SARS-CoV-2: Highlighting drug target sites.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is a highly transmittable and pathogenic human coronavirus that first emerged in China in December 2019. The unprecedented outbreak of SARS-CoV-2 devastated human health within a short time leading to a global public health emergency. A detailed understanding of the viral proteins including their structural characteristics and virulence mechanism on human health is very crucial for developing vaccines and therapeutics. To date, over 1800 structures of non-structural, structural, and accessory proteins of SARS-CoV-2 are determined by cryo-electron microscopy, X-ray crystallography, and NMR spectroscopy. Designing therapeutics to target the viral proteins has several benefits since they could be highly specific against the virus while maintaining minimal detrimental effects on humans. However, for ongoing and future research on SARS-CoV-2, summarizing all the viral proteins and their detailed structural information is crucial. In this review, we compile comprehensive information on viral structural, non-structural, and accessory proteins structures with their binding and catalytic sites, different domain and motifs, and potential drug target sites to assist chemists, biologists, and clinicians finding necessary details for fundamental and therapeutic research.

LRFMV: An efficient customer segmentation model for superstores.

The Recency, Frequency, and Monetary model, also known as the RFM model, is a popular and widely used business model for determining beneficial client segments and analyzing profit. It is also recommended and frequently used in superstores to identify customer segments and increase profit margins. Later, the Length, Recency, Frequency, and Monetary model, also known as the LRFM model, was introduced as an improved version of the RFM model to identify more relevant and exact consumer groups for profit maximization. Superstores have a varying number of different products. In RFM and LRFM models, the relationship between profit and purchased quantity has never been investigated. Therefore, this paper proposed an efficient customer segmentation model, namely LRFMV (Length, Recency, Frequency, Monetary and Volume) and studied the profit-quantity relationship. A new dimension V (volume) has been added to the existing LRFM model to show a direct profit-quantity relationship in customer segmentation. The V stands for volume, which is derived by calculating the average number of products purchased by a frequent superstore client in a single day. The data obtained from feature extraction of the LRMFV model is then clustered by using conventional K-means, K-Medoids, and Mini Batch K-means methods. The results obtained from the three algorithms are compared, and the K-means algorithm is chosen for the superstore dataset of the proposed LRFMV model. All clusters created using these three algorithms are evaluated in the LRFMV model, and a close relationship between profit and volume is observed. A clear profit-quantity relationship of items has yet not been seen in any prior study on the RFM and LRFM models. Grouping customers aiming at profit maximization existed previously, but there was no clear and direct depiction of profit and quantity of sold items. This study applied unsupervised machine learning to investigate the patterns, trends, and correlations between volume and profit. The traits of all the clusters are analyzed by the Customer-Classification Matrix. The LRFMV values, larger or less than the overall average for each cluster, are identified as their traits. The performance of the proposed LRFMV model is compared with the legacy RFM and LRFM customer segmentation models. The outcome shows that the LRFMV model creates precise customer segments with the same number of customers while maintaining a greater profit.

Recent advances in extraction of chitin and chitosan.

Chitosan is a versatile biopolymer due to its biocompatibility, biodegradability, antimicrobial, non-toxic, mucoadhesive, and highly adsorptive properties. Chitosan and its derivatives have been used for many biomedical applications. Currently, crustacean shells and other marine organisms are the significant sources of chitin/chitosan production worldwide. However, extraction from marine sources presents several challenges, including an unstable supply of raw materials. Large-scale chitosan extraction from crustacean sources harms the environment by involving harsh processing steps such as alkali deproteinization. Recently many studies have been carried out focusing on alternative sources or eco-friendlier routes for production of chitosan. This paper briefly overviews recent studies on fungi and insect cuticles as alternative chitosan sources. Milder extraction processes for fungal chitosan and the superior quality of the resultant polymer make it highly desirable for biological applications. Biological techniques involving fermentation and enzymatic processing of the raw materials are looked at in detail. In the concluding remarks, the paper highlights the potential of using a combination of "green" technologies and briefly looks at potential biological/biomedical applications of extracted chitinous materials.

Evaluating the Prognostic and Therapeutic Potentials of the Proteasome 26S Subunit, ATPase (PSMC) Family of Genes in Lung Adenocarcinoma: A Database Mining Approach.

This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.

Ecological Burden of e-Waste in Bangladesh-an Assessment to Measure the Exposure to e-Waste and Associated Health Outcomes: Protocol for a Cross-sectional Study.

BACKGROUND: e-Waste is a rapidly growing waste stream worldwide, and Bangladesh is a hub of e-waste handling. Informal e-waste recycling operations involve crude methods for dismantling, repairing, sorting, and recycling electronic goods with bare hands and without personal health protections. Direct inhalation or dermal exposure to toxicants during informal recycling is common. Evidence suggests that e-waste-derived toxicants pollute the terrestrial ecosystem and have been linked with adverse health effects. However, e-waste recycling-related occupational health hazards have not been adequately explored in the context of Bangladesh. OBJECTIVE: Our study aims to expand the current understanding of exposure to e-waste. This study will measure the metal concentrations in biological and environmental samples and evaluate the relationship between heavy metals and the biochemical systems of the e-waste workers. METHODS: The study uses a cross-sectional study design consisting of an exposed site and a nonexposed control site. The trained team collected information on individual exposures, detailed work and medical history, and biological samples (blood, urine, and hair) from each subject. This study will measure heavy metal levels (lead, cadmium, and mercury) and biochemical parameters (hematological, hormonal, renal, and others) from the biological samples with reported physical function as outcomes of interest. In addition, we also collected soil and dust samples from both exposed and nonexposed control sites to measure the health risk. All the environmental samples will be analyzed using inductively coupled plasma mass spectrometer to determine metal concentrations. We will also conduct a qualitative investigation for a deeper understanding of the e-waste management system in Bangladesh. RESULTS: The protocol has been approved by the Institutional Review Boards of the International Centre for Diarrheal Disease Research, Bangladesh, and The University of Queensland's Human Behavioral Ethics Committee. Informed written consent was obtained from all participants. We recruited 199 workers from the e-waste sites with at least 5 years of exposure and 104 control subjects with no industrial or e-waste exposure. Sample analysis is estimated to be completed in 2022. CONCLUSIONS: Although many studies have identified potential adverse health outcomes from exposure to e-waste, there is a lack of published epidemiological research in Bangladesh. Research in this field is particularly pressing in the context of the current e-waste trend and the need to deepen the understanding of exposures and outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38201.

Age and gender-related differences in quality of life of Bangladeshi patients with Down Syndrome: A cross-sectional study.

Currently available screening instruments for evaluation of individuals with intellectual disabilities do not capture all the complications associated with Down Syndrome (DS). Here, we examined age and gender-specific variability revolving around major challenges related to ophthalmologic and auditory health, social integration, daily life, and behavioral problems in 468 (age: 2-84 years) individuals with DS living in all eight divisions of Bangladesh. More than half of the children presented with significant difficulty in walking or other targeted movements compared with 37.9% of adolescents (p = 0.03). Nearly 70% of children exhibited communication difficulties, particularly revolving around the understanding of speech, comprehending or learning tasks or new materials, and in expressing thoughts in words or behaviors (p = 0.003-0.006). Uncontrolled urination was frequent and predominantly found among children (p = 0.04). No significant differences were present in females vs. males except for concern about physical appearance (females: 58.5% vs. males: 47.5%; p = 0.02). The severity of DS was associated with intellectual performance, communication difficulties, and self-sufficiency (i.e., uncontrolled micturition or bowel movements) but not with psychotic, ophthalmologic, auditory, or motor skills-related problems. Increased awareness of DS phenotypic profiles among professionals and caregivers can foster earlier detection and counselling and help formulate appropriate interventions to reduce long-term sequelae and enhance cognitive and behavioral developmental outcomes.

Progress and challenges of contaminate removal from wastewater using microalgae biomass.

The utilization of microalgae in treating wastewater has been an emerging topic focussed on finding an economically sustainable and environmentally friendly approach to treating wastewater. Over the last several years, different types of con microalgae and bacteria consortia have been experimented with to explore their potential in effectively treating wastewater from different sources. The basic features considered while determining efficiency is their capacity to remove nutrients including nitrogen (N) and phosphorus (P) and heavy metals like arsenic (As), lead (Pb), and copper (Cu). This paper reviews the efficiency of microalgae as an approach to treating wastewater from different sources and compares conventional and microalgae-based treatment systems. The paper also discusses the characteristics of wastewater, conventional methods of wastewater treatment that have been used so far, and the technological mechanisms for removing nutrients and heavy metals from contaminated water. Microalgae can successfully eliminate the suspended nutrients and have been reported to successfully remove N, P, and heavy metals by up to 99.6 %, 100 %, and 13%-100 % from different types of wastewater. However, although a microalgae-based wastewater treatment system offers some benefits, it also presents some challenges as outlined in the last section of this paper. Performance in eliminating nutrients from wastewater is affected by different parameters such as temperature, biomass productivity, osmotic ability, pH, O2 concentration. Therefore, the conducting of pilot-scale studies and exploration of the complexities of contaminants under complex environmental conditions is recommended.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV).

OBJECTIVES: The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options. METHODS: In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2. RESULTS: The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine. CONCLUSION: If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

Influence on attitudes and lifestyle due to lockdown amidst COVID-19 pandemic: a perception-based analysis among Bangladeshi residents.

BACKGROUND: Countrywide lockdown or stay-at-home order has been implemented to slow down the transmission of emergent coronavirus. However, the influence on attitudes and lifestyle due to lockdown amidst the coronavirus disease 2019 (COVID-19) pandemic has been poorly understood. The present study aimed to investigate the influence on attitudes and lifestyle due to lockdown amidst the COVID-19 pandemic among Bangladeshi residents. METHODS: A cross-sectional survey carried out involving 1635 community dwellers across eight divisions in Bangladesh conducted from April 15, 2020 to May 10, 2020. A structured questionnaire incorporating socio-demographic, attitudes towards lockdown and adverse lifestyle amidst lockdown measures was employed to collect data using the Google Forms. Multiple regression analyses were executed to determine the associated factors of positive attitudes towards lockdown and adverse lifestyle. RESULTS: The mean scores of attitudes towards lockdown were 67.9 (SD = 8.4) out of 85 with an overall correct rate (positive attitudes) of 79.9%; whereas the mean scores of adverse lifestyle amidst lockdown were 16.1 (SD = 4.8) out of 34 with an overall rate of 47.4%. The factors associated with more positive attitudes towards lockdown included being female, divorced, higher educated, and students. Conversely, being male, having no formal education, and rural residence were associated factors of adverse lifestyle amidst the COVID-19 pandemic. CONCLUSIONS: The findings reflect how the COVID-19 lockdown has preciously impacted the attitudes, and lifestyle of Bangladeshi citizens, which will contribute to promoting appropriate measures during a subsequent zonal or complete lockdown.

Saccharomyces Cerevisiae as an Untapped Source of Fungal Chitosan for Antimicrobial Action.

Despite being widely available, Saccharomyces cerevisiae has not been widely explored for direct extraction of chitosan biopolymer for antimicrobial applications. In our study, S. cerevisiae from Baker's yeast and Aspergillus niger from moldy onion extracts are studied as alternative sources of chitosan; and S cerevisiae chitosan tested for antimicrobial efficacy. The properties of S. cerevisiae chitosan are compared with moldy onion chitosan and shrimp chitosan extracted from shrimp shells. Chitosan extracted from S. cerevisiae is tested for antimicrobial efficacy against Staphylococcus Aureus. The maximum yields of fungal chitosan are 20.85 ± 0.35 mg/g dry S. cerevisiae biomass at 4th day using a culture broth containing sodium acetate, and 16.15 ± 0.95 mg/g dry A. niger biomass at 12th day. The degree of deacetylation (DD%) of the extracted fungal chitosan samples from S. cerevisiae and A. niger is found to be 63.4%, and 61.2% respectively, using Fourier Transform Infrared Spectroscopy. At a concentration of 2 g/L, S. cerevisiae chitosan shows the maximum inhibition zone diameter of 15.48 ± 0.07 mm. Baker's yeast S cerevisiae biomass and A. niger from moldy onions has not been previously explored as a source of extractible fungal chitosan. This study gives insight that S. cerevisiae and A. niger from agricultural or industrial wastes could be a potential biomass source for production of the chitosan biopolymer. The S. cerevisiae chitosan displayed effective antimicrobial properties against S aureus, indicating the viablitiy of S cerevisae as a resource for extraction of high-quality chitosan.

Drought dynamics of Northwestern Teesta Floodplain of Bangladesh: a remote sensing approach to ascertain the cause and effect.

Drought is an affliction for a region that primarily depends on agriculture as economic activity. Commonly monitoring and characterizing of drought is performed by only analyzing the meteorological aspect, assuming precipitation as the primary source of water. However, in riverine Bangladesh, this can lead to an erroneous conclusion, as there is a multitude of available water sources. Consequently, in this study, vegetation condition (Standard Vegetation Index), soil moisture (Soil Moisture Index), and precipitation (Standard Precipitation Index) are separately investigated from 2003 to 2019, in the Northwestern Teesta floodplain. Subsequently, statistical regression analysis is performed to determine the relationships between different aspects of drought. In addition, information obtained from field visits and expert opinions has also been assimilated. Analysis of vegetation and soil moisture condition presents a progressively improving scenario. However, SPI shows an incessant decline in meteorological drought conditions, especially after 2007. Evidently, regression analysis does not provide any indication of an interrelationship between the studied agricultural and meteorological parameters. Presumably, this absence is instigated because the study area is highly irrigated as the groundwater table is suitably near the surface and the existence of nearby Teesta river allows for the utilization of surface water. Moreover, the cropping pattern is shifting toward crops that require much less water and to places where soil moisture is scarce. Thus, this study addresses the gap in knowledge regarding the nature of agricultural drought and the dynamics of different aspects of drought which will be invaluable for the water management and agricultural policy in the study area as well as other regions with a similar backdrop.

Use of a Branched Linker for Enhanced Biosensing Properties in IgG Detection from Mixed Chinese Hamster Ovary Cell Cultures.

Tris(2-aminoethyl)-amine (TREN), a branched amine, was coupled to planar surfaces of alkanethiol self-assembled monolayers (SAMs) to increase the grafting density of IgG-binding peptide (HWRGWV or HWRGWVG) on gold surfaces. One of the three primary amine pendant groups of TREN anchors onto the SAM, while the other two are available for grafting with the C-termini of the peptide. The ellipsometric peptide density on the SAM-branched amine was 1.24 molecules nm-2. The surfaces carrying the peptides were investigated via surface plasmon resonance (SPR) to quantify the adsorption of IgG and showed maximum binding capacity, Qm of 4.45 mg m-2, and dissociation constant, Kd of 8.7 × 10-7 M. Real-time dynamic adsorption data was used to determine adsorption rate constants, ka values, and the values were dependent on IgG concentration. IgG binding from complex mixtures of Chinese hamster ovary supernatant (CHO) was investigated and regeneration studies were carried out. Compared to the unbranched amine-based surfaces, the branched amines increased the overall sensitivity and selectivity for IgG adsorption from complex mixtures. Regeneration of the branched amine-based surfaces was achieved with 0.1 M NaOH, with less than 10% decline in peptide activity after 12 cycles of regeneration-binding.

High resolution melting curve analysis enables rapid and reliable detection of G6PD variants in heterozygous females.

BACKGROUND: Like glucose-6-phosphate dehydrogenase (G6PD) deficient hemizygous males and homozygous females, heterozygous females could also manifest hemolytic crisis, neonatal hyperbilirubinemia or kernicterus upon exposure to oxidative stress induced by certain foods such as fava beans, drugs or infections. Although hemizygous males and homozygous females are easily detected by conventional G6PD enzyme assay method, the heterozygous state could be missed by the conventional methods as the mosaic population of both normal and deficient RBCs circulates in the blood. Thus the present study aimed to apply high resolution melting (HRM) curve analysis approach to see whether HRM could be used as a supplemental approach to increase the chance of detection of G6PD heterozygosity. RESULTS: Sixty-three clinically suspected females were evaluated for G6PD status using both enzyme assay and HRM analysis. Four out of sixty-three participants came out as G6PD deficient by the enzyme assay method, whereas HRM approach could identify nine participants with G6PD variants, one homozygous and eight heterozygous. Although only three out of eight heterozygous samples had G6PD enzyme deficiency, the HRM-based heterozygous G6PD variants detection for the rest of the samples with normal G6PD enzyme activities could have significance because their newborns might fall victim to serious consequences under certain oxidative stress. CONCLUSIONS: In addition to the G6PD enzyme assay, HRM curve analysis could be useful as a supplemental approach for detection of G6PD heterozygosity.

CLIP and cohibin separate rDNA from nucleolar proteins destined for degradation by nucleophagy.

Nutrient starvation or inactivation of target of rapamycin complex 1 (TORC1) in budding yeast induces nucleophagy, a selective autophagy process that preferentially degrades nucleolar components. DNA, including ribosomal DNA (rDNA), is not degraded by nucleophagy, even though rDNA is embedded in the nucleolus. Here, we show that TORC1 inactivation promotes relocalization of nucleolar proteins and rDNA to different sites. Nucleolar proteins move to sites proximal to the nuclear-vacuolar junction (NVJ), where micronucleophagy (or piecemeal microautophagy of the nucleus) occurs, whereas rDNA dissociates from nucleolar proteins and moves to sites distal to NVJs. CLIP and cohibin, which tether rDNA to the inner nuclear membrane, were required for repositioning of nucleolar proteins and rDNA, as well as effective nucleophagic degradation of the nucleolar proteins. Furthermore, micronucleophagy itself was necessary for the repositioning of rDNA and nucleolar proteins. However, rDNA escaped from nucleophagic degradation in CLIP- or cohibin-deficient cells. This study reveals that rDNA-nucleolar protein separation is important for the nucleophagic degradation of nucleolar proteins.