Genetic gains in IRRI's rice salinity breeding and elite panel development as a future breeding resource.

KEY MESSAGE: Estimating genetic gains and formulating a future salinity elite breeding panel for rice pave the way for developing better high-yielding salinity tolerant lines with enhanced genetic gains. Genetic gain is a crucial parameter to check the breeding program's success and help optimize future breeding strategies for enhanced genetic gains. To estimate the genetic gains in IRRI's salinity breeding program and identify the best genotypes based on high breeding values for grain yield (kg/ha), we analyzed the historical data from the trials conducted in the IRRI, Philippines and Bangladesh. A two-stage mixed-model approach accounting for experimental design factors and a relationship matrix was fitted to obtain the breeding values for grain yield and estimate genetic trends. A positive genetic trend of 0.1% per annum with a yield advantage of 1.52 kg/ha was observed in IRRI, Philippines. In Bangladesh, we observed a genetic gain of 0.31% per annum with a yield advantage of 14.02 kg/ha. In the released varieties, we observed a genetic gain of 0.12% per annum with a 2.2 kg/ha/year yield advantage in the IRRI, Philippines. For the Bangladesh dataset, a genetic gain of 0.14% per annum with a yield advantage of 5.9 kg/ha/year was observed in the released varieties. Based on breeding values for grain yield, a core set of the top 145 genotypes with higher breeding values of > 2400 kg/ha in the IRRI, Philippines, and > 3500 kg/ha in Bangladesh with a reliability of > 0.4 were selected to develop the elite breeding panel. Conclusively, a recurrent selection breeding strategy integrated with novel technologies like genomic selection and speed breeding is highly required to achieve higher genetic gains in IRRI's salinity breeding programs.

Electronic aggregated data collection on cervical cancer screening in Bangladesh since 2014: what the data tells us?

INTRODUCTION: To reduce the high prevalence of cervical cancers among the Bangladeshi women, the Government of Bangladesh established a national cervical cancer screening programme in 2005 for women aged 30 to 60 years. The District Health Information System Version 2 (DHIS2) based electronic aggregated data collection system is used since the year 2013. This study summarises data from the year 2014 to 2022 to assess the effectiveness of the electronic data collection system in understanding the outcome of the screening programme. METHODS: This is a descriptive study based on secondary data extracted in MS Excel from the DHIS2-based electronic repository of the national cervical cancer screening programme of Bangladesh. The respondents were women aged 30-60 years, screened for cervical cancer using VIA (Visual Inspection of cervix with Acetic acid) method in 465 government health facilities. The data were collected on the participants' residential location, month and year of screening, name and type of health facilities performing VIA, and VIA screening results. RESULTS: The national screening programme reported a total 3.36 million VIA tests from 465 government hospitals in 8 years (2014 to 2022). The national average VIA-positivity rate was 3.6%, which varied from 1.4 to 9.5% among the districts. This national screening programme witnessed an exponential growth, year after year, with 83.3% increase in VIA test from 2014 to 2022. The primary and the secondary care hospitals were the highest collective contributors of VIA tests (86.2%) and positive cases (77.8%). The VIA-positivity rates in different hospital types varied widely, 7.0% in the medical university hospital, 5.7% in the medical college hospitals, 3.9% in the district/general hospitals, and 3.0% in the upazila health complexes. CONCLUSIONS: A national cervical cancer screening programme using VIA method and a DHIS2-based electronic data collection backbone, is effective, sustainable, and useful to understand the screening coverage, VIA positivity rate and geographic distribution of the participants and case load to initiate policy recommendations and actions. Decentralization of the screening programme and more efforts at the primary and secondary care level is required to increase screening performances.

Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin.

The co-occurrence of migraine and glycemic traits has long been reported in observational epidemiological studies, but it has remained unknown how they are linked genetically. We used large-scale GWAS summary statistics on migraine, headache, and nine glycemic traits in European populations to perform cross-trait analyses to estimate genetic correlation, identify shared genomic regions, loci, genes, and pathways, and test for causal relationships. Out of the nine glycemic traits, significant genetic correlation was observed for fasting insulin (FI) and glycated haemoglobin (HbA1c) with both migraine and headache, while 2-h glucose was genetically correlated only with migraine. Among 1703 linkage disequilibrium (LD) independent regions of the genome, we found pleiotropic regions between migraine and FI, fasting glucose (FG), and HbA1c, and pleiotropic regions between headache and glucose, FI, HbA1c, and fasting proinsulin. Cross-trait GWAS meta-analysis with glycemic traits, identified six novel genome-wide significant lead SNPs with migraine, and six novel lead SNPs with headache (Pmeta < 5.0 × 10-8 and Psingle-trait < 1 × 10-4), all of which were LD-independent. Genes with a nominal gene-based association (Pgene ≤ 0.05) were significantly enriched (overlapping) across the migraine, headache, and glycemic traits. Mendelian randomisation analyses produced intriguing, but inconsistent, evidence for a causal relationship between migraine and headache with multiple glycemic traits; and consistent evidence suggesting increased fasting proinsulin levels may causally decrease the risk of headache. Our findings indicate that migraine, headache, and glycemic traits share a common genetic etiology and provide genetic insights into the molecular mechanisms contributing to their comorbid relationship.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

50 years of rice breeding in Bangladesh: genetic yield trends.

To assess the efficiency of genetic improvement programs, it is essential to assess the genetic trend in long-term data. The present study estimates the genetic trends for grain yield of rice varieties released between 1970 and 2020 by the Bangladesh Rice Research Institute. The yield of the varieties was assessed from 2001-2002 to 2020-2021 in multi-locations trials. In such a series of trials, yield may increase over time due to (i) genetic improvement (genetic trend) and (ii) improved management or favorable climate change (agronomic/non-genetic trend). In both the winter and monsoon seasons, we observed positive genetic and non-genetic trends. The annual genetic trend for grain yield in both winter and monsoon rice varieties was 0.01 t ha-1, while the non-genetic trend for both seasons was 0.02 t ha-1, corresponding to yearly genetic gains of 0.28% and 0.18% in winter and monsoon seasons, respectively. The overall percentage yield change from 1970 until 2020 for winter rice was 40.96%, of which 13.91% was genetic trend and 27.05% was non-genetic. For the monsoon season, the overall percentage change from 1973 until 2020 was 38.39%, of which genetic and non-genetic increases were 8.36% and 30.03%, respectively. Overall, the contribution of non-genetic trend is larger than genetic trend both for winter and monsoon seasons. These results suggest that limited progress has been made in improving yield in Bangladeshi rice breeding programs over the last 50 years. Breeding programs need to be modernized to deliver sufficient genetic gains in the future to sustain Bangladeshi food security.

Artificial intelligence in glaucoma: opportunities, challenges, and future directions.

Artificial intelligence (AI) has shown excellent diagnostic performance in detecting various complex problems related to many areas of healthcare including ophthalmology. AI diagnostic systems developed from fundus images have become state-of-the-art tools in diagnosing retinal conditions and glaucoma as well as other ocular diseases. However, designing and implementing AI models using large imaging data is challenging. In this study, we review different machine learning (ML) and deep learning (DL) techniques applied to multiple modalities of retinal data, such as fundus images and visual fields for glaucoma detection, progression assessment, staging and so on. We summarize findings and provide several taxonomies to help the reader understand the evolution of conventional and emerging AI models in glaucoma. We discuss opportunities and challenges facing AI application in glaucoma and highlight some key themes from the existing literature that may help to explore future studies. Our goal in this systematic review is to help readers and researchers to understand critical aspects of AI related to glaucoma as well as determine the necessary steps and requirements for the successful development of AI models in glaucoma.

The Effect of Dataset Imbalance on the Performance of SCADA Intrusion Detection Systems.

Integrating IoT devices in SCADA systems has provided efficient and improved data collection and transmission technologies. This enhancement comes with significant security challenges, exposing traditionally isolated systems to the public internet. Effective and highly reliable security devices, such as intrusion detection system (IDSs) and intrusion prevention systems (IPS), are critical. Countless studies used deep learning algorithms to design an efficient IDS; however, the fundamental issue of imbalanced datasets was not fully addressed. In our research, we examined the impact of data imbalance on developing an effective SCADA-based IDS. To investigate the impact of various data balancing techniques, we chose two unbalanced datasets, the Morris power dataset, and CICIDS2017 dataset, including random sampling, one-sided selection (OSS), near-miss, SMOTE, and ADASYN. For binary classification, convolutional neural networks were coupled with long short-term memory (CNN-LSTM). The system's effectiveness was determined by the confusion matrix, which includes evaluation metrics, such as accuracy, precision, detection rate, and F1-score. Four experiments on the two datasets demonstrate the impact of the data imbalance. This research aims to help security researchers in understanding imbalanced datasets and their impact on DL SCADA-IDS.

Modification with Conventional Surfactants to Improve a Lipid-Based Ionic-Liquid-Associated Transcutaneous Anticancer Vaccine.

Transcutaneous vaccination is one of the successful, affordable, and patient-friendly advanced immunization approaches because of the presence of multiple immune-responsive cell types in the skin. However, in the absence of a preferable facilitator, the skin's outer layer is a strong impediment to delivering biologically active foreign particles. Lipid-based biocompatible ionic-liquid-mediated nanodrug carriers represent an expedient and distinct strategy to permit transdermal drug delivery; with acceptable surfactants, the performance of drug formulations might be further enhanced. For this purpose, we formulated a lipid-based nanovaccine using a conventional (cationic/anionic/nonionic) surfactant loaded with an antigenic protein and immunomodulator in its core to promote drug delivery by penetrating the skin and boosting drug delivery and immunogenic cell activity. In a follow-up investigation, a freeze-dry emulsification process was used to prepare the nanovaccine, and its transdermal delivery, pharmacokinetic parameters, and ability to activate autoimmune cells in the tumor microenvironment were studied in a tumor-budding C57BL/6N mouse model. These analyses were performed using ELISA, nuclei and HE staining, flow cytometry, and other biological techniques. The immunomodulator-containing nanovaccine significantly (p < 0.001) increased transdermal drug delivery and anticancer immune responses (IgG, IgG1, IgG2, CD8+, CD207+, and CD103+ expression) without causing cellular or biological toxicity. Using a nanovaccination approach, it is possible to create a more targeted and efficient delivery system for cancer antigens, thereby stimulating a stronger immune response compared with conventional aqueous formulations. This might lead to more effective therapeutic and preventative outcomes for patients with cancer.

Exploring avoidable presentations from residential aged care facilities to the emergency department of a large regional Australian hospital.

OBJECTIVES: The study aimed at determining the factors that contributed to older people presenting from residential aged care facilities (RACFs) to the emergency department (ED) of a regional Victorian hospital located in MM3 regional area. METHODS: Appropriateness of transfer was assessed based on predefined criteria, and associated costs for each presentation were calculated. DESIGN: The study carried out a retrospective review of records between July and December 2021. Data were extracted in a MS Excel spreadsheet and transferred to STATA 15.0 for analysis. SETTING: Large regional health service in Victoria. PARTICIPANTS: Residential aged care facilities residents presenting to the ED. MAIN OUTCOME MEASURES: Was transfer appropriate or avoidable, costs associated with avoidable transfer, characteristics of the patient and circumstances relating to presentation to hospital. RESULTS: A total of 448 presentations were recorded, and 85% of residents were >75 years of age. More than 60% of presentations occurred during weekends or after hours, with the most common reason being falls (31.9%). Over half (55.6%) of all presentations were avoidable which incurred a cost of $777 200 in 6 months. In multiple logistic regression, higher ED presentations were observed in residents with no prior GP assessment (OR: 1.47, 95% CI: 1.02-2.11). CONCLUSIONS: Necessary interventions such as preventing falls and increasing primary care access along with improving the quality of advance care directives (ACD) may reduce RACF transfers to the regional ED. To the best of our knowledge, this is the first paper of this kind that provides new data from an Australian rural and regional perspective and adds value to the growing body of knowledge in the intersection of aged care and acute emergency care.

The development and psychometric evaluation of COVID-19 staff questionnaire for infectious disease outbreak readiness and preparedness (SQIDORP).

BACKGROUND: The COVID-19 pandemic has inundated the capacity of hospitals across the globe, exhausting resources, and placing extreme burden on health care workers (HCWs). Hospital preparedness during infectious disease outbreak involves development and implementation of appropriate strategies, procedures, and adequate training for HCWs. Reliable and valid tools to evaluate the perception of HCWs on the effectiveness of hospital preparedness strategies are imperative and literature is yet to fill that gap. METHODS: Items for 'The Staff Questionnaire for Infectious Disease Outbreak Readiness and Preparedness (SQIDORP)' were selected from literature that addressed hospital preparedness during novel pandemic outbreaks. The SQIDORP was distributed within a regional hospital in Victoria, Australia. Psychometric evaluation included estimates of reliability and factor analysis while factors associated with the questionnaire were explored using regression analysis. RESULTS: Omega coefficient of 0.89, Cronbach's alpha coefficient of 0.88 and item-total correlations (> 0.3) indicated adequate reliability of the SQIDORP. Factor Analysis yielded three meaningful latent factors that are effectiveness of training (Factor 1), self-confidence (Factor 2) and risk to self and stress (Factor 3). Demographic factors did not influence the correlation with SQIDORP. However, rating 'the current plan for management of COVID-19 in your ward' and 'personal knowledge/skills in caring for patients with COVID-19' had significant positive correlation and accounted for 33% of the variance in readiness and preparedness using SQIDORP (R2 = 0.33, F = 10.227, P < 0.001). CONCLUSION: Most of the items of SQIDORP questionnaire achieved adequate internal consistence reliability. This is a valuable tool that can be utilized by hospitals to explore aspects of preparedness and give insights to the knowledge, skills, and mental health of HCWs, as perceived by the HCW themselves.

Cell Volume-Activated and Volume-Correlated Anion Channels in Mammalian Cells: Their Biophysical, Molecular, and Pharmacological Properties.

There are a number of mammalian anion channel types associated with cell volume changes. These channel types are classified into two groups: volume-activated anion channels (VAACs) and volume-correlated anion channels (VCACs). VAACs can be directly activated by cell swelling and include the volume-sensitive outwardly rectifying anion channel (VSOR), which is also called the volume-regulated anion channel; the maxi-anion channel (MAC or Maxi-Cl); and the voltage-gated anion channel, chloride channel (ClC)-2. VCACs can be facultatively implicated in, although not directly activated by, cell volume changes and include the cAMP-activated cystic fibrosis transmembrane conductance regulator (CFTR) anion channel, the Ca2+-activated Cl- channel (CaCC), and the acid-sensitive (or acid-stimulated) outwardly rectifying anion channel. This article describes the phenotypical properties and activation mechanisms of both groups of anion channels, including accumulating pieces of information on the basis of recent molecular understanding. To that end, this review also highlights the molecular identities of both anion channel groups; in addition to the molecular identities of ClC-2 and CFTR, those of CaCC, VSOR, and Maxi-Cl were recently identified by applying genome-wide approaches. In the last section of this review, the most up-to-date information on the pharmacological properties of both anion channel groups, especially their half-maximal inhibitory concentrations (IC50 values) and voltage-dependent blocking, is summarized particularly from the standpoint of pharmacological distinctions among them. Future physiologic and pharmacological studies are definitely warranted for therapeutic targeting of dysfunction of VAACs and VCACs.

A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage's Influence in a Malaysian Palm Oil Plantation Environment.

Palm oil is the main cash crop of tropical Asia, and the implementation of LPWAN (low-power wide-area network) technologies for smart agriculture applications in palm oil plantations will benefit the palm oil industry in terms of making more revenue. This research attempts to characterize the LoRa 433 MHz frequency channels for the available spreading factors (SF7-SF12) and bandwidths (125 kHz, 250 kHz, and 500 kHz) for wireless sensor networks. The LoRa channel modeling in terms of path-loss calculation uses empirical measurements of RSS (received signal strength) in a palm oil plantation located in Selangor, Malaysia. In this research, about 1500 LoS (line-of-sight) and 300 NLoS (non-line-of-sight) propagation measurement data are collected for path-loss prediction modeling. Using the empirical data, a prediction model is constructed. The path-loss exponent for LoS propagation of the proposed prediction model is found to be 2.34 and 2.9 for 125-250 kHz bandwidth and 500 kHz bandwidth, respectively. Again, for the NLoS propagation links, the attenuation per trunk is found to be 7.58 dB, 7.04 dB, 5.35 dB, 5.02 dB, 5.01 dB, and 5 dB for SF7-SF12, and the attenuation per canopy is found to be 9.32 dB, 7.96 dB, 6.2 dB, 5.89 dB, 5.79 dB, and 5.45 dB for SF7-SF12. Moreover, the prediction model is found to be the better choice (mean RMSE 2.74 dB) in comparison to the empirical foliage loss models (Weissberger's and ITU-R) to predict the path loss in palm oil plantations.

Child and Adolescent Mental Health Training Programs for Non-specialist Mental Health Professionals in Low and Middle Income Countries: A Scoping Review of Literature.

Large treatment deficits in child and adolescent mental health (CAMH) care exist in low and middle income countries (LMICs). This study reviewed CAMH training programs for non-specialist health professionals (NSHPs) in LMICs. Multiple databases were searched for peer-reviewed articles describing programs from 2005 to 2018. Educational source materials, trainee evaluation methods, and perspectives on teaching methods, course content and scheduling were studied. Six programs were identified. NSHPs were most appreciative of training which included case-based discussions, role plays and clinical demonstrations that were relevant to local contexts. A need for less intense and more flexible timetables to enable reflection was identified. WHO's mental health gap action program intervention guide (mhGAP-IG) and international association of child and adolescent psychiatrists and allied professionals resources should be used; they are free, easily accessible, and developed with extensive international contributions. Additionally, mhGAP-IG assessment tool encourages mutual learning, thereby iteratively enhancing training programs.

Mitigating greenhouse gas emissions from irrigated rice cultivation through improved fertilizer and water management.

Greenhouse gas (GHG) emissions from agriculture sector play an important role for global warming and climate change. Thus, it is necessary to find out GHG emissions mitigation strategies from rice cultivation. The efficient management of nitrogen fertilizer using urea deep placement (UDP) and the use of the water-saving alternate wetting and drying (AWD) irrigation could mitigate greenhouse gas (GHG) emissions and reduce environmental pollution. However, there is a dearth of studies on the impacts of UDP and the integrated plant nutrient system (IPNS) which combines poultry manure and prilled urea (PU) with different irrigation regimes on GHG emissions, nitrogen use efficiency (NUE) and rice yields. We conducted field experiments during the dry seasons of 2018, 2019, and 2020 to compare the effects of four fertilizer treatments including control (no N), PU, UDP, and IPNS in combination with two irrigation systems- (AWD and continuous flooding, CF) on GHG emissions, NUE and rice yield. Fertilizer treatments had significant (p < 0.05) interaction effects with irrigation regimes on methane (CH4) and nitrous oxide (N2O) emissions. PU reduced CH4 and N2O emissions by 6% and 20% compared to IPNS treatment, respectively under AWD irrigation, but produced similar emissions under CF irrigation. Similarly, UDP reduced cumulative CH4 emissions by 9% and 15% under AWD irrigation, and 9% and 11% under CF condition compared to PU and IPNS treatments, respectively. Across the year and fertilizer treatments, AWD irrigation significantly (p < 0.05) reduced cumulative CH4 emissions and GHG intensity by 28%, and 26%, respectively without significant yield loss compared to CF condition. Although AWD irrigation increased cumulative N2O emissions by 73%, it reduced the total global warming potential by 27% compared to CF irrigation. The CH4 emission factor for AWD was lower (1.67 kg ha-1 day-1) compared to CF (2.33 kg ha-1 day-1). Across the irrigation regimes, UDP increased rice yield by 21% and N recovery efficiency by 58% compared to PU. These results suggest that both UDP and AWD irrigation might be considered as a carbon-friendly technology.

The organic anion transporter SLCO2A1 constitutes the core component of the Maxi-Cl channel.

The maxi-anion channels (MACs) are expressed in cells from mammals to amphibians with ~60% exhibiting a phenotype called Maxi-Cl. Maxi-Cl serves as the most efficient pathway for regulated fluxes of inorganic and organic anions including ATP However, its molecular entity has long been elusive. By subjecting proteins isolated from bleb membranes rich in Maxi-Cl activity to LC-MS/MS combined with targeted siRNA screening, CRISPR/Cas9-mediated knockout, and heterologous overexpression, we identified the organic anion transporter SLCO2A1, known as a prostaglandin transporter (PGT), as a key component of Maxi-Cl. Recombinant SLCO2A1 exhibited Maxi-Cl activity in reconstituted proteoliposomes. When SLCO2A1, but not its two disease-causing mutants, was heterologously expressed in cells which lack endogenous SLCO2A1 expression and Maxi-Cl activity, Maxi-Cl currents became activated. The charge-neutralized mutant became weakly cation-selective with exhibiting a smaller single-channel conductance. Slco2a1 silencing in vitro and in vivo, respectively, suppressed the release of ATP from swollen C127 cells and from Langendorff-perfused mouse hearts subjected to ischemia-reperfusion. These findings indicate that SLCO2A1 is an essential core component of the ATP-conductive Maxi-Cl channel.

Genome-wide association mapping of sodium and potassium concentration in rice grains and shoots under alternate wetting and drying and continuously flooded irrigation.

KEY MESSAGE: Identification of a large number of QTL and candidate genes for sodium accumulation in a field grown population of rice derived from the aus subpopulation. Rice (Oryza sativa L.) is a globally important cereal crop. Sodium (Na+) and potassium (K+) are the major monovalent ions which affect rice growth, and exploring their uptake mechanisms will be useful for understanding rice biology. Since the balance of Na+ and K+ plays a significant role in adaptation of rice to salinity, that biology might inform the search for tolerance. In this study, the Na+ and K+ concentration and Na+/K+ ratio in grains and shoots were analyzed in the Bengal and Assam Aus Panel grown in field conditions under continuously flooded (CF) and alternate wetting and drying (AWD) irrigation. Overall, AWD irrigation significantly reduced the Na+ concentration and increased the K+ concentration in shoots and grains compared to the plants grown under CF. Genome-wide association mapping was conducted on Na+, K+ concentration and Na+/K+ ratio with 2 million SNPs using an efficient mixed model. Only QTLs which contained more than two significant SNPs (p < 0.0001) and where at least one of these significant SNPs passed a 10% false discovery rate were reported. A total of 106 QTLs were identified as being associated with Na+ concentration and Na+/K+ ratio across all traits and field conditions, with 48 QTLs found in multiple traits and/or water conditions. Four notable QTLs (one each on chromosomes 1 and 11, two on chromosome 2) and the haplotype variants of four candidate genes (OsHKT1;5, OsNHX2, LOC_Os02g32490 and OsFAD2_1) are discussed. The QTLs/candidate genes identified here could be useful for breeding rice that accumulates lower concentrations of sodium.

Growth kinetics of a Vero cells adapted Bangladeshi strain of peste des petits ruminants (PPR) virus in cell culture.

Growth kinetics of a Vero cells adapted Bangladeshi strain of peste des petits ruminants virus was studied in Vero cells to determine maximum virus yield. One-step growth curve was formulated after determining virus in both supernatant (CFV) and cell lysate (CAV) at different time categories by microtitre plate titration in Vero cells and the viral presence was confirmed by real-time RT-PCR. The virus was first detected in both the supernatants and cell pellets at 12 hpi. The virus titre reached its plateau at 72 hpi. Maximum virus titre of CAV was 6.2 log10 TCID50/ml and that of CFV was 5.2 log10 TCID50/ml at 72 hpi. After that, the titer gradually declined, but maintained at 4.5 log10 TCID50/ml in case of CAV and 4.2 log10 TCID50/ml in case of CFV at 96 hpi. It was concluded that the optimum time point for harvesting Vero cell culture is 72 hpi.

First molecular characterization and phylogenetic analysis of the VP2 gene of feline panleukopenia virus in Bangladesh.

Feline panleukopenia virus (FPV) is a highly contagious infectious pathogen of cats globally. However, there is no information on the molecular identification and characterization of FPV in Bangladesh. Here, 8.16% (8/98) and 18.37% (18/98) of diarrheic cats tested positive for FPV by an immunochromatography (IC) test and PCR, respectively. The IC test showed 44.44% sensitivity and 100% specificity in comparison with PCR. Our newly sequenced Bangladeshi FPV strain (MN826076) showed the highest (99.71%) sequence identity to strains from the United Arab Emirates (UAE). Strain MN826076 contained two characteristic amino acid variations in VP2 identifying it as an FPV strain: valine at position 103 and aspartic acid at position 323. Phylogenetically, the VP2 of strain MN826076 was found to be closely related to 19 FPV strains, sharing the same clade.

Annexin A2-S100A10 Represents the Regulatory Component of Maxi-Cl Channel Dependent on Protein Tyrosine Dephosphorylation and Intracellular Ca²âº.

BACKGROUND/AIMS: Maxi-anion channel (Maxi-Cl) is ubiquitously expressed and involved in a number of important cell functions especially by serving as an ATP release pathway. We recently identified SLCO2A1 as its essential core component. However, the regulatory component required for the channel activation/inactivation remains unidentified. METHODS: In the present study, to identify the regulatory component, we made genome-wide analysis combined with siRNA screening and performed patch-clamp studies and ATP release assay after gene silencing and overexpression. RESULTS: Comparative microarray analysis between Maxi-Cl-rich C127 and -deficient C1300 cells revealed highly differential expression not only of SLCO2A1 but also of four annexin family members. Gene silencing study showed that Anxa2 is involved in Maxi-Cl activity. The Maxi-Cl events appeared in C1300 cells by overexpression of Slco2a1 and more efficiently by that of Slco2a1 plus Anxa2. Immunoprecipitation assay supported the interaction between ANXA2 and SLCO2A1. Suppressive effects of overexpression of a phospho-mimicking mutant of Anxa2, Anxa2-Y23E, indicated that protein tyrosine dephosphorylation dependence of Maxi-Cl is conferred by ANXA2. Maxi-Cl activity was suppressed by gene silencing of S100A10, a binding partner of ANXA2, and by applying a synthetic ANXA2 peptide, Ac-(1-14), which interferes with the ANXA2-S100A10 complex formation. Intracellular Ca2+ dependence of Maxi-Cl activity was abolished by S100a10 knockdown. CONCLUSION: The ANXA2-S100A10 complex represents the regulatory component of Maxi-Cl conferring protein tyrosine dephosphorylation dependence and intracellular Ca2+ sensitivity on this channel.

Characterization, identification and expression profiling of genome-wide R-genes in melon and their putative roles in bacterial fruit blotch resistance.

BACKGROUND: Bacterial fruit blotch (BFB), a disease caused by Acidovorax citrulli, results in significant economic losses in melon. The causal QTLs and genes for resistance to this disease have yet to be identified. Resistance (R)-genes play vital roles in resistance to plant diseases. Since the complete genome sequence of melon is available and genome-wide identification of R-genes has been performed for this important crop, comprehensive expression profiling may lead to the identification of putative candidate genes that function in the response to BFB. RESULTS: We identified melon accessions that are resistant and susceptible to BFB through repeated bioassays and characterized all 70 R-genes in melon, including their gene structures, chromosomal locations, domain organizations, motif distributions, and syntenic relationships. Several disease resistance-related domains were identified, including NBS, TIR, LRR, CC, RLK, and DUF domains, and the genes were categorized based on the domains of their encoded proteins. In addition, we profiled the expression patterns of the genes in melon accessions with contrasting levels of BFB resistance at 12 h, 1 d, 3 d, and 6 d after inoculation with A. citrulli. Six R-genes exhibited consistent expression patterns (MELO3C023441, MELO3C016529, MELO3C022157, MELO3C022146, MELO3C025518, and MELO3C004303), with higher expression levels in the resistant vs. susceptible accession. CONCLUSION: We identified six putative candidate R-genes against BFB in melon. Upon functional validation, these genes could be targeted for manipulation via breeding and biotechnological approaches to improve BFB resistance in melon in the future.