Effects of diabetes mellitus on retreatment of Tuberculosis: A multi-centered case-control study from Bangladesh.

Objectives: Several studies suggested that diabetes mellitus (DM) worsens the tuberculosis (TB) treatment outcome. But information regarding the association of DM with retreatment of TB is very scarce in Bangladesh. Present study aimed to assess the effects of DM on retreatment of TB. Methods: This case-control study was conducted among 254 patients (127 cases and 127 controls) from January 2022 - December 2022. Patients were recruited by purposive sampling from 92 centers of the Diabetic Association of Bangladesh (BADAS). Data were collected by face-to-face interview and record reviewing with the help of semi-structured questionnaire and checklist respectively. Quality of data was maintained in all stages of the study. Data were analyzed by using IBM SPSS software. Informed written consent was taken from each patient prior to the study. Ethical issues were maintained strictly. Results: Present study matched the age and sex of cases and controls. The study revealed that majority of case (89.0) and controls (97.6) were married. Among cases 78.0 % had DM and among controls 64.6 % had DM. Among diabetic patients, 78.8 % cases' and 64.6 % controls' HbA1C level was not within normal range. The study found that, the number of episodes of previous TB (AOR = 3.088, ρ = 0.019), presence of DM (AOR = 2.817, ρ = 0.012) and uncontrolled HbA1C level (AOR = 2.500, ρ = 0.028) were independently associated with retreatment of TB. Conclusion: The study found that presence of DM, uncontrolled HbA1C level and multiple episodes of previous TB were the risk factors for retreatment of TB. So, a separate guideline for treatment of TB-DM patients should be established to prevent retreatment cases.

E2EE enhanced patient-centric blockchain-based system for EHR management.

To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments.

Nutritional status of children with neurodevelopmental disorders: a cross-sectional study at a tertiary-level hospital in northern Bangladesh.

BACKGROUND: Malnutrition in children with neurodevelopmental disorders (NDDs) is a significant global public health issue. Nutritional assessment combined with management or advice are essential to produce optimal outcomes. OBJECTIVES: The objective of this study was to assess nutritional status and the sociodemographic profile of children with neurodevelopmental disorders in Bangladesh. METHODS: A cross-sectional study was conducted from December to April 2020 among the population of children with NDDs who presented to the pediatric department of the TMSS Medical College and Rafatullah Community Hospital in Bogura during this period. Socio-demographic data along with anthropometric measurements of the children were taken. Assessment of nutritional status were made using metrics such as z-scores for weight-for-age (WAZ), height-for-age (HAZ), and body mass index-for-age (BAZ). Descriptive statistics (number and percentage) and analytical statistics (chi-square and logistic regression) were included. RESULTS: 58.6% of children displayed malnutrition, with 47.8% showing undernutrition (WHZ / BAZ - 1 SD-≤-3 SD), and 10.8% overnutrition (BAZ > 2SD). Significant negative associations were found between malnutrition and parental education level, urban residency, and monthly family income. Children diagnosed with cerebral palsy exhibited twice the likelihood to be malnourished (AOR 2.39, 95% CI 0.83-6.87). Furthermore, residing in rural regions was associated with an increased risk of experiencing malnutrition, as indicated by an adjusted odds ratio of 1.60 (95% CI 0.12-3.09). CONCLUSIONS: While the results are cross-sectional, over half of children with NDDs were found to be malnourished, suggesting that children with NDD in Bangladesh are vulnerable to developing any form of malnutrition. Therefore, regular assessments and timely nutritional support may improve their situation.

Antibacterial potential of lactic acid bacteria isolated from raw cow milk in Sylhet district, Bangladesh: A molecular approach.

BACKGROUND: The most prevalent probiotic bacterium employed in the food industry is Lactobacillus because it can produce metabolites with antibacterial capabilities and exhibits hostility towards infections and microorganisms that cause spoilage. AIM: This study set out to identify naturally occurring Lactobacillus and plantaricin (pln EF) coding genes in raw cow milk and to assess the antibacterial potency of isolated Lactobacillus isolates. METHODS: Following enrichment in De Man, Rogosa and Sharpe (MRS) broth, single colonies were isolated, and pure colonies were obtained by streaking on MRS agar. The 16S rRNA gene was amplified using polymerase chain reaction (PCR) to confirm the cultural positivity of all isolates. Additionally, the presence of plantaricin was verified by targeting the pln EF gene through PCR. OUTCOME: Out of the 166 raw milk specimens acquired from cows, 153 (91.17%; CI: 86.98-95.76) were identified as positive for Lactobacillus through both culture and biochemical screening. Subsequently, 121 (72.89%; CI: 65.46-79.49) of the isolates were affirmed to harbour Lactobacillus through PCR analysis. Within this subset, 6 isolates (4.96%; CI: 1.84-10.48) were found to possess the plnEF gene. When exposed to Lactobacillus isolates, Salmonella Typhimurium and Salmonella enterica displayed an average maximum zone of inhibition with a diameter measuring 24 mm. In contrast, Escherichia coli exhibited an average minimum zone of inhibition, featuring a diameter of 11 mm. Additionally, the Lactobacillus isolates demonstrated inhibitory zones against Staphylococcus aureus, Klebsiella pneumoniae and Klebsiella oxytoca, measuring 14, 22 and 19 mm, respectively. CLINICAL SIGNIFICANCE: Lactic acid bacteria, particularly Lactobacilli, are plentiful in cow milk and possess broad-spectrum antibacterial properties.

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.

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.

Numerical modeling of a MHD non-linear radiative Maxwell nano fluid with activation energy.

The present research explores linear as well as nonlinear radiation patterns based on the MHD non-Newtonian (Maxwell) nanofluid flow having Arrhenius activation energy. This study's core focus is MHD properties in non-Newtonian fluid dynamics and boundary layer phenomena analysis. It initiates with time-dependent equations, employing boundary layer approximations. Extensive numerical computations, executed with custom Compact Visual Fortran code and the EFD method, provide profound insights into non-Newtonian fluid behavior, revealing intricate force interactions and fluid patterns. To check the stability of the solution, a convergence and stability analysis is performed. With the values of ΔY = 0.25, Δτ = 0.0005, and ΔX = 0.20; it is found that the model convergence occurs to the Lewis number, Le > 0.016 as well as the Prandtl number, Pr > 0.08. In this context, investigating non-dimensional results that depend on multiple physical factors. Explanation and visual representations of the effects of different physical characteristics and their resultant temperatures, concentrations, and velocity profiles are provided. As a result of the illustrations, the skin friction coefficient and Sherwood number, which are calculated, as well as Nusselt values, have all come up in discussion. Additionally, detailed representations of isothermal lines and streamlines are implemented, and it is pointed out that the development of these features occurs at the same time as Brownian motion. Furthermore, the temperature field for Maxwell fluid is modified due to the impression of chemical reaction as well as the Dufour number (Kr and Du). Our research demonstrates the superior performance of non-Newtonian solutions, notably in cases involving activation energy and nonlinear radiation. This paradigm shift carries significant implications. In another context, the interplay between Maxwell fluid and nonlinear radiation is notably affected by activation energy, offering promising applications in fields like medicine and industry, particularly in groundbreaking cancer treatment approaches.

Study on the genetic variability and adaptability of turmeric (Curcuma longa L.) genotypes for development of desirable cultivars.

Turmeric, a globally cultivated spice, holds significance in medicine, and cosmetics, and is also a very popular ingredient in South Asian cuisine. A study involving 53 turmeric genotypes evaluated for rhizome yield and related traits at Spices Research Center, Bogura, Bangladesh over three years (2019-22). A randomized complete block design was followed with two replications. ANOVA revealed significant trait variations among genotypes. Genotype T0015 emerged as the highest yielder at 28.04 t/ha. High heritability (0.58-0.99) and genetic advance characterized plant height (PH), mother rhizome weight (WMR), primary and secondary finger weights (WPF and WSF), and yield per plant (YPP) across seasons. Genetic gain (GG) was prominent in these traits. Genotypic and phenotypic coefficient variations (GCV and PCV) (6.24-89.46 and 8.18-90.88, respectively) across three years highlighted mother rhizome weight's importance followed by numbers of primary finger (NPF), and WPF. Positive and significant correlations, especially with PH, WMR, WPF, and YPP, emphasized their relevance to fresh yield (FY). Multiple linear regression identified PH, number of mother rhizome (NMR) and WMR as key contributors, explaining 37-79% of FY variability. Cluster analysis grouped genotypes into five clusters with maximum distance observed between clusters II and III. The geometric adaptability index (GAI) assessed adaptability and superiority, revealing nine genotypes outperforming the best existing cultivar. Genotype T0117 as the top performer based on GAI, followed by T0103 and T0094. Mean rank analysis favoured T0121 as the best performer, succeeded by T0117, T0082 and T0106. The top ten genotypes (T0015, T0061, T0082, T0085, T0094, T0103, T0106, T0117, T0121 and T0129) were identified as superior based on yield and overall ranking, warranting further evaluation. These findings may induce a window for improving turmeric research and ultimately play a role in enhancing its cultivation and productivity.

Effects of integrated plant nutrition systems with fertilizer deep placement on rice yields and nitrogen use efficiency under different irrigation regimes.

Improved fertilizer management, with a combination of organic and inorganic inputs, has the potential to enhance rice yield while maintaining soil health. However, studies on the effects of broadcast prilled urea (PU) and urea deep placement (UDP) applied in combination with organic inputs (poultry litter [PL] and vermicompost [VC]), as integrated plant nutrition systems (IPNSs), on rice yields and nitrogen use efficiency (NUE) under alternate wetting and drying (AWD) irrigation are limited. We conducted field experiments during the dry and wet seasons of 2018, 2019, and 2020 to investigate the effects of fertilizer treatments, including control (no nitrogen), UDP, PU, and IPNSs (PU + VC, PU + PL, and UDP + PL) on rice yield and NUE under two irrigation regimes - AWD and continuous flooding (CF). The results revealed that fertilizer treatment and irrigation regime had significant (p < 0.05) interaction effects on rice yield and the agronomic efficiency of N (AEN) during the dry season. UDP significantly (p < 0.05) boosted rice yield, total dry matter (TDM), and NUE as compared to broadcast PU in both wet and dry seasons. Similarly, the IPNS treatment of UDP with PL significantly (p < 0.05) boosted rice yield, TDM, and NUE in comparison to broadcast PU. Under AWD irrigation, UDP alone produced higher rice yields than other treatments, while UDP, and UDP with PL produced similar yields under CF irrigation. During the dry season, AWD irrigation significantly (p < 0.05) increased rice yield, TDM, and AEN when compared to CF conditions, but during the wet season, AWD irrigation demonstrated a rice yield and NUE equivalent to CF. This research implies that using a UDP alone or in combination with PL as an IPNS could be a good way to boost crop productivity while also maintaining soil fertility.

Protection of the third-dose and fourth-dose mRNA vaccines against SARS-CoV-2 Omicron subvariant: a systematic review and meta-analysis.

OBJECTIVES: The rapid spread of the SARS-CoV-2 Omicron variant has raised concerns regarding waning vaccine-induced immunity and durability. We evaluated protection of the third-dose and fourth-dose mRNA vaccines against SARS-CoV-2 Omicron subvariant and its sublineages. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Electronic databases and other resources (PubMed, Embase, CENTRAL, MEDLINE, CINAHL PLUS, APA PsycINFO, Web of Science, Scopus, ScienceDirect, MedRxiv and bioRxiv) were searched until December 2022. STUDY ELIGIBILITY CRITERIA: We included studies that assessed the effectiveness of mRNA vaccine booster doses against SARS-CoV-2 infection and severe COVID-19 outcomes caused by the subvariant. DATA EXTRACTION AND SYNTHESIS: Estimates of vaccine effectiveness (VE) at different time points after the third-dose and fourth-dose vaccination were extracted. Random-effects meta-analysis was used to compare VE of the third dose versus the primary series, no vaccination and the fourth dose at different time points. The certainty of the evidence was assessed by Grading of Recommendations, Assessments, Development and Evaluation approach. RESULTS: This review included 50 studies. The third-dose VE, compared with the primary series, against SARS-CoV-2 infection was 48.86% (95% CI 44.90% to 52.82%, low certainty) at ≥14 days, and gradually decreased to 38.01% (95% CI 13.90% to 62.13%, very low certainty) at ≥90 days after the third-dose vaccination. The fourth-dose VE peaked at 14-30 days (56.70% (95% CI 50.36% to 63.04%), moderate certainty), then quickly declined at 61-90 days (22% (95% CI 6.40% to 37.60%), low certainty). Compared with no vaccination, the third-dose VE was 75.84% (95% CI 40.56% to 111.12%, low certainty) against BA.1 infection, and 70.41% (95% CI 49.94% to 90.88%, low certainty) against BA.2 infection at ≥7 days after the third-dose vaccination. The third-dose VE against hospitalisation remained stable over time and maintained 79.30% (95% CI 58.65% to 99.94%, moderate certainty) at 91-120 days. The fourth-dose VE up to 60 days was 67.54% (95% CI 59.76% to 75.33%, moderate certainty) for hospitalisation and 77.88% (95% CI 72.55% to 83.21%, moderate certainty) for death. CONCLUSION: The boosters provided substantial protection against severe COVID-19 outcomes for at least 6 months, although the duration of protection remains uncertain, suggesting the need for a booster dose within 6 months of the third-dose or fourth-dose vaccination. However, the certainty of evidence in our VE estimates varied from very low to moderate, indicating significant heterogeneity among studies that should be considered when interpreting the findings for public health policies. PROSPERO REGISTRATION NUMBER: CRD42023376698.

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.

An analytical investigation of critical factors to prioritize coalfields for Underground Coal Gasification - Bangladesh case.

In recent decades, many countries have shown a growing interest in Underground Coal Gasification (UCG) as a potential clean and environmental-friendly means of harnessing coal energy for power generation, and production of hydrogen, diesel fuel, etc. While Bangladesh may have good UCG potential that can be utilized to alleviate the country's current energy scarcity, this avenue has remained completely untapped up to now. In this work, the possibility of UCG implementation in five (05) indigenous discovered coalfields of the country was evaluated for the first time by using the preference selection index (PSI) method. This novel technique was considered to prioritize coalfields for gauging UCG potential. The PSI method is chosen over numerous traditional multi-criteria decision-making (MCDM) techniques, because it selects the best alternative from given alternatives without deciding the relative importance between attributes. The study indicated Jamalganj coalfield as the most suitable for implementing the UCG technique with a 93.6% potential. The second priority is Khalaspir coalfield with around 70.0% prospect and the other three coalfields - Dighipara (64.7%), Barapukuria (63.5%), and Phulbari (58.3%) may have UCG suitability in decreasing order of preference. The deduction is expected to assist the cogitation of energy-sector researchers and facilitate the decision-making of relevant authorities, policy makers, planners, and entrepreneurs.

Hybrid imaging of prompt x-rays and induced positrons using a pinhole gamma camera during and after irradiation of protons.

Objective. Prompt x-ray imaging using a low-energy x-ray camera is a promising method for observing a proton beam's shape from outside the subject. Furthermore, imaging of positrons produced by nuclear reactions with protons is a possible method for observing the beam shape. However, it has not been possible to measure these two types of images with a single imaging system due to the limited imaging capability of existing systems. Imaging of both prompt x-rays and the distribution of positrons may compensate for the shortcomings of each method.Approach. We conducted imaging of the prompt x-ray using a pinhole x-ray camera during irradiation with protons in list mode. Then, after irradiation with protons, imaging of annihilation radiations from the produced positrons was conducted using the same pinhole x-ray camera in list mode. After this imaging, list-mode data were sorted to obtain prompt x-ray images and positron images.Main results. With the proposed procedure, we could measure both prompt x-ray images and induced positron images with a single irradiation by a proton beam. From the prompt x-ray images, ranges and widths of the proton beams could be estimated. The distributions of positrons were slightly wider than those of the prompt x-rays. From the time sequential positron images, we could derive the time activity curves of the produced positrons.Significance. Hybrid imaging of prompt x-rays and induced positrons using a pinhole x-ray camera was achieved. The proposed procedure would be useful for measuring prompt x-ray images during irradiation to estimate the beam structures as well as for measuring the induced positron images after irradiation to estimate the distributions and time activity curves of the induced positrons.

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.

Performance valuation of onion (Allium cepa L.) genotypes under different levels of salinity for the development of cultivars suitable for saline regions.

Abiotic stress, especially salt stress, is one of the major barriers to crop production worldwide. Crops like onion that belong to the glycophytic group are more sensitive to salinity stress. A huge study regarding the influence of salinity stress on the growth and development of crops has already been done and is still ongoing. One of the major targets of the research is to develop genotypes that have enhanced performance under stress environments. The world needs more of these types of genotypes to combat the ever-growing salt-stressed soils. Therefore, a number of germplasm were studied during the 2019-2020 and 2020-2021 seasons under different salt concentrations to identify tolerant genotypes as well as to study the plants' responses at different growth stages against elevated salinity levels. A 2-year study was conducted where germination potential was evaluated in the first year and carried out in petri dish culture of seeds, followed by plastic pot culture for plant establishment and bulb development evaluation during the second year. Four different saline water solutions having different salt concentrations (0, 8, 10, and 12 dS m-1) were applied to the petri dishes and pots as the source of water for plants in both seasons. Results indicated that a significant reduction in plants' performance occurs under higher salinity levels. Salt concentration had an adverse impact on germination, leaf development and growth, the height of plants, bulb size and shape, and the bulb weight of onion. All the growth phases of onion are sensitive to elevated concentrations. Variable performances were observed in the genotypes under stress conditions, and a few genotypes (Ac Bog 409, Ac Bog 414, Ac Bog 424, Ac Bog 430, Ac Bog 417, Ac Bog 419, Ac Bog 420, Ac Bog 422, and Ac Bog 425) having some sort of tolerance to salt stress were identified, which might be recommended for mass production. Tolerance indices could successfully be applied in selecting the salt-tolerant genotypes. Thus, the present findings and the identified genotypes could be further utilized in salt stress improvement research on onion.

Identification of Essential Protein Using Chemical Reaction Optimization and Machine Learning Technique.

For the survival, development, and reproduction of the organism, understanding the working process of the cell, disease study, design drugs, etc. essential protein plays a crucial role. Due to a large number of biological information, computational methods are becoming popular in recent times to identify the essential protein. Many computational methods used machine learning techniques, metaheuristic algorithms, etc. to solve the problem. The problem with these methods is that the essential protein class prediction rate is still low. Many of these methods have not considered the imbalance characteristics of the dataset. In this paper, we have proposed an approach to identify essential proteins using a metaheuristic algorithm named Chemical Reaction Optimization (CRO) and machine learning method. Both topological and biological features are used here. The Saccharomyces cerevisiae (S. cerevisiae) and Escherichia coli (E. coli) datasets are used in the experiment. Topological features are calculated from the PPI network data. Composite features are calculated from the collected features. Synthetic Minority Over-sampling Technique and Edited Nearest Neighbor (SMOTE+ENN) technique is applied to balance the dataset and then the CRO algorithm is applied to achieve the optimal number of features. Our experiment shows that the proposed approach gives better results in both accuracy and f-measure than the existing related methods.

Comparison between Acid Digestion (ICP-OES) and X-ray Fluorescence (XRF) Spectrometry for Zinc Concentration Determination in Rice (Oryza sativa L.).

The determination of mineral concentrations in rice grain samples is crucial for analyzing their nutritional content. Most mineral content analysis techniques depend on inductively coupled plasma (ICP) spectrometry and are often complicated, expensive, time-consuming, and laborious. Recently, the handheld X-ray fluorescence (XRF) spectrometer has been randomly used in earth sciences; however, it is hardly practiced in quantifying mineral content in rice samples. In this research, the reliability of XRF results was compared with that of the ICP-OES to determine zinc (Zn) concentration in rice (Oryza sativa L.). Approximately 200 dehusked rice samples and four known high-Zn samples were analyzed using both XRF and ICP-OES techniques. The concentrations of Zn were recorded using the XRF technique and then correlated with the ICP-OES results. The results indicated a high positive relationship between two methods, with R2 = 0.83, p = 0.000, and the Pearson correlation value of 0.91 at the level of 0.05. This work demonstrates the potential of XRF as a reliable and low-cost as well as an alternative technique to ICP-OES methods for determining Zn content in rice as it allows the analysis of a greater number of samples in a short period at a considerably low price.

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.

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.

Multi-environment Genomic Selection in Rice Elite Breeding Lines.

BACKGROUND: Assessing the performance of elite lines in target environments is essential for breeding programs to select the most relevant genotypes. One of the main complexities in this task resides in accounting for the genotype by environment interactions. Genomic prediction models that integrate information from multi-environment trials and environmental covariates can be efficient tools in this context. The objective of this study was to assess the predictive ability of different genomic prediction models to optimize the use of multi-environment information. We used 111 elite breeding lines representing the diversity of the international rice research institute breeding program for irrigated ecosystems. The lines were evaluated for three traits (days to flowering, plant height, and grain yield) in 15 environments in Asia and Africa and genotyped with 882 SNP markers. We evaluated the efficiency of genomic prediction to predict untested environments using seven multi-environment models and three cross-validation scenarios. RESULTS: The elite lines were found to belong to the indica group and more specifically the indica-1B subgroup which gathered improved material originating from the Green Revolution. Phenotypic correlations between environments were high for days to flowering and plant height (33% and 54% of pairwise correlation greater than 0.5) but low for grain yield (lower than 0.2 in most cases). Clustering analyses based on environmental covariates separated Asia's and Africa's environments into different clusters or subclusters. The predictive abilities ranged from 0.06 to 0.79 for days to flowering, 0.25-0.88 for plant height, and - 0.29-0.62 for grain yield. We found that models integrating genotype-by-environment interaction effects did not perform significantly better than models integrating only main effects (genotypes and environment or environmental covariates). The different cross-validation scenarios showed that, in most cases, the use of all available environments gave better results than a subset. CONCLUSION: Multi-environment genomic prediction models with main effects were sufficient for accurate phenotypic prediction of elite lines in targeted environments. These results will help refine the testing strategy to update the genomic prediction models to improve predictive ability.