Cost-effective Method Research Articles

Implementation of a university-wide health-system collaborative to provide pharmacy preceptor development across multiple institutions

Abstract Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose The University of California Preceptor Development Collaborative was established in 2022 across 5 academic medical centers and 3 schools of pharmacy. The collaborative aimed to streamline preceptor development efforts, enhance collaboration, and meet accreditation standards efficiently by providing quarterly preceptor development programming across all sites to residency and school preceptors. This article describes the implementation of the collaborative and assesses the number of attendees, attendee satisfaction, and cost during the pilot year. Summary During the pilot year, 5 live virtual preceptor development modules were developed for pharmacist preceptors. There were 631 credit hours claimed (196 from session 1, 106 from session 2, 68 from session 3, 123 from session 4, and 138 from session 5). Preceptor satisfaction, as measured from completed postsession evaluations (n = 704), was high (a median score of 5 on a Likert scale where 1 = none at all, 2 = a little, 3 = a moderate amount, 4 = a lot, and 5 = a great deal) for meeting educational, professional, teaching, or clinical needs. There was strong agreement (median score of 5 on Likert scale where 1 = strongly disagree, 2 = somewhat disagree, 3 = neither agree nor disagree, 4 = somewhat agree, and 5 = strongly agree) that the modules improved knowledge, ability to change practice, and ability to have positive impacts on trainees and patients. The cost per attendee for this series was $1.58 per continuing education credit. Conclusion A multi-institution state-wide preceptor collaborative effort produced quarterly continuing education for residency and school of pharmacy preceptors who were affiliated with the sites. This approach to preceptor development is a convenient, satisfactory, and cost-effective method to deliver training for pharmacy preceptors.

A sustainable HPTLC approach for green assessment of Tyrosine to phenylalanine ratio in chronic kidney disease

AbstractThe kidney is considered the main site for the net release of Tyrosine (Tyr) to the circulation through hydroxylation of Phenylalanine (Phe) using phenylalanine hydroxylase enzyme. In chronic kidney disease (CKD) patients the enzyme activity is impaired, therefore the serum concentration ratio of Tyr/Phe is reduced compared to healthy individuals. This motivates us to develop a cost effective, green, simple, sensitive, and selective HPTLC method to measure the levels of Tyr and Phe in serum samples. The analysis was carried out using acetonitrile: ethanol: 25% ammonia solution: ethyl acetate (6.5: 1.5: 1: 0.5) as a mobile phase. Rf values were 0.55 ± 0.05 for Phe and 0.39 ± 0.05 for Tyr. Densitometry scanning was performed using UV detector and dual wavelengths of 210 and 225 nm were obtained. A linear correlation was observed between the levels of Phe and Tyr, ranging from 50 to 700 ng band− 1 and 50 to 600 ng band− 1, respectively, under the optimum conditions. The method selectivity, linearity, precision, accuracy, and robustness were all confirmed in accordance with ICH recommendations. Calculations of the separation and resolution factors, number of theoretical plates, and height equivalent to theoretical plates prove to the chromatographic system accuracy and high separation efficiency. The developed method exhibits an acceptable eco-scale when measuring the method greenness using AGREE and GAPI softwares. It was applied for the determination of Phe and Tyr concentrations in human serum samples.

Photosynthetic efficiency and water retention in okra (Abelmoschus esculentus) contribute to tolerance to single and combined effects of drought and heat stress.

The co-occurrence of drought and heat significantly hampers plant productivity. Although their impacts are well studied, these studies have been based on the effects of individual stressors rather than their combined influence. Okra is crucial for food and nutritional security and livelihoods in many regions, yet it remains under-researched and unimproved. Okra has been proven to be sensitive to both drought and heat stress. This study employed a cost-effective phenotyping method to assess key traits characterising the diversity of okra morphophysiological responses to independent and interactive heat-drought stresses. This study aimed to understand okra responses to stress, identify stress-resilient traits, and characterise okra genotypes. We also addressed the need to examine interactive stress effects, which mirror real-world scenarios more accurately than single-stress studies. Sixty-three okra genotypes were subjected to heat, drought, or concurrent heat-drought stress at the seedling stage in improvised climate-controlled chambers. The germplasm exhibited significant variations in response to the various stresses. The broad-sense heritability was high (> 0.60) for traits such as chlorophyll content, plant biomass, performance indices, electrolyte leakage, and total leaf area. Drought stress alone had a more pronounced effect than heat stress alone, and the adverse impact was worsened under combined heat and drought stress. The interactive impact of drought and heat was more likely additive than antagonistic or synergistic. A positive and strong relationship was observed between photosynthetic efficiency parameters such as the Fv/Fm ratio, chlorophyll content, relative water index, and biomass parameters such as dry shoot weight. The 63 okra genotypes were classified into three distinct clusters, suggesting potential for future breeding efforts. Okra genotype considered to be tolerant or climate resilient (such as GH170, V1060831, GH174, V1060874, and GH106) to drought and heat, maintained enhanced photosynthetic efficiency and high internal water potential, possibly reducing osmotic and oxidative damage. This study revealed some mechanisms underlying the adaptation of okra genotypes to independent and combined heat and drought stress. The results provide a basis for breeding efforts to develop climate-resilient okra varieties.

Empirical versus estimated accuracy of imputation: optimising filtering thresholds for sequence imputation.

Genotype imputation is a cost-effective method for obtaining sequence genotypes for downstream analyses such as genome-wide association studies (GWAS). However, low imputation accuracy can increase the risk of false positives, so it is important to pre-filter data or at least assess the potential limitations due to imputation accuracy. In this study, we benchmarked three different imputation programs (Beagle 5.2, Minimac4 and IMPUTE5) and compared the empirical accuracy of imputation with the software estimated accuracy of imputation (Rsqsoft). We also tested the accuracy of imputation in cattle for autosomal and X chromosomes, SNP and INDEL, when imputing from either low-density or high-density genotypes. The accuracy of imputing sequence variants from real high-density genotypes was higher than from low-density genotypes. In our software benchmark, all programs performed well with only minor differences in accuracy. While there was a close relationship between empirical imputation accuracy and the imputation Rsqsoft, this differed considerably for Minimac4 compared to Beagle 5.2 and IMPUTE5. We found that the Rsqsoft threshold for removing poorly imputed variants must be customised according to the software and this should be accounted for when merging data from multiple studies, such as in meta-GWAS studies. We also found that imposing an Rsqsoft filter has a positive impact on genomic regions with poor imputation accuracy due to large segmental duplications that are susceptible to error-prone alignment. Overall, our results showed that on average the imputation accuracy for INDEL was approximately 6% lower than SNP for all software programs. Importantly, the imputation accuracy for the non-PAR (non-Pseudo-Autosomal Region) of the X chromosome was comparable to autosomal imputation accuracy, while for the PAR it was substantially lower, particularly when starting from low-density genotypes. This study provides an empirically derived approach to apply customised software-specific Rsqsoft thresholds for downstream analyses of imputed variants, such as needed for a meta-GWAS. The very poor empirical imputation accuracy for variants on the PAR when starting from low density genotypes demonstrates that this region should be imputed starting from a higher density of real genotypes.

Unveiling Community Needs and Aspirations: Card Sorting as a Research Method for Developing Digital Learning Spaces

<p style="text-align:justify">This pilot study is part of a larger “Decolonization of Digital Learning Spaces” project, which aims to develop research tools for communities that are remote and/or excluded geographically, politically, economically, socially, culturally, and linguistically. The project’s ultimate goal is to work alongside these communities to design their own digital learning tools, networks, and online educational environments by accessing and leveraging their knowledge and skills. Testing the single-criterion card sorting method is the first step toward this goal. Card sorting is an easy, enjoyable, and cost-effective method for data collection and analysis, particularly for researchers working in remote areas with limited access to electricity or the Internet. The pilot explored single-criterion card sorting as a method to elicit knowledge from two diverse cultural and linguistic groups engaged in learning activities within their communities. These groups were from a Deaf and Hard of Hearing (DHH) community in Canada (engaged in a bow-making workshop) and a rural Kabyle community in Algeria (engaged in a traditional cooking lesson). Despite low participant numbers, distinct patterns emerged, indicating the method's effectiveness. The results, though anticipated, were non-random, demonstrating the potential of card sorting in producing patterns indicative of how individuals and/or communities categorize their world(s). Kabyle sortings focused on ingredients, highlighting older individuals as teachers passing along knowledge, while the DHH sortings emphasized face-to-face contact and hand movements in communication. The findings, though modest, established relationships, provided insights into the research context and offered logistical understanding, paving the way for further work with DHH and Kabyle communities towards the design of digital learning spaces.</p>

Development and Validation of Rapid and Cost-Effective RP-HPLC/UV Method for Determination of Cetirizine/Levocetirizine in Blood Plasma of Smokers and Non Smokers: a Two Cohort Comparative Study.

In this research study, a simple, rapid, sensitive, and cost-effective Reverse Phase High Performance Liquid Chromatography method was developed and validated for determination of Cetirizine and Levocetirizine in human plasma. The drugs were separated on an ACE Generix100-5 C18 RP (250 × 4.6mm, 5μm) column, using Acetonitrile and Distilled water pH7 (59:41v/v) as mobile phase with a flow rate of 1.5mL/min, retention time of 3.39 ± 0.02min, detection wavelength of 230nm, and column oven temperature at 26°C. The drug was extracted from human plasma using Methanol, the percent recovery was 97%. The LOD and LOQ for Cetirizine and Levocetirizine were 0.5ng and 1ng. The method was linear over the concentration range of 0.5-1000ng /mL for Cetirizine and Levocetirizine. The method was applied for analysis of drugs in plasma following oral administration of Cetirizine (10mg) and Levocetirizine (5mg) in smokers and nonsmokers of Pashtun ethnicity belonging from different districts of Khyber Pakhtunkhwa, Pakistan. The difference between Cetirizine plasma levels in smokers and non-smokers was significant with p -value 0.0279.

Pesticide pollution: toxicity, sources and advanced remediation approaches.

The Food and Agricultural Organization of the United Nations (FAO) estimates that food production must rise by 70% to meet the demands of an additional 2.3 billion people by 2050. This forecast underscores the persistent reliance on pesticides, making it essential to assess their toxicity and develop effective remediation strategies. Given the widespread utilisation of pesticides, it requires an urgent need to evaluate their toxicity and explore feasible remediation approaches for their removal. Hence, this review provides an overview of the latest information on the presence, distribution, sources, fate, and trends of pesticides in global environmental matrices, emphasizing the ecological and health risks posed by pesticide pollution. Currently, the dominant remediation techniques encompass physical, chemical, and biological methods, yet studies focusing on advanced remediation techniques remain limited. This review critically evaluates both newer and traditional approaches to pesticide removal, offering a descriptive and analytical comparison of various methods. The selection of the appropriate treatment method depends largely on the nature of the pesticide and the effectiveness of the chosen technique. In many cases, technologies such as membrane bioreactors and the fenton process could be integrated with biological technologies to enhance performance and overcome limitations. The study concludes that a hybrid approach combining various remediation strategies offers the most effective and sustainable solution for pesticide removal. Finally, the review underscores the need for further scientific investigation into the most viable technologies while discussing the challenges and prospects of developing safe, reliable, cost-effective, and eco-friendly methods for removing pesticides from the environment.

Effectiveness of cold atmospheric plasma in decontaminating enterococcus faecalis colonized collagen and PTFE membranes used in guided bone regeneration: a comparative in vitro investigation.

Wound healing disorders caused by bacterial infections in dental surgery, especially where membranes are used, are a common issue in oral surgery. Cold atmospheric plasma (CAP) offers a non-invasive solution for surface decontamination, including dental implants. The aim of this study was to evaluate the antibacterial effectiveness of CAP on various clinically applied membranes made of collagen and polytetrafluoroethylene (PTFE). To assess the antibacterial properties of CAP, enterococcus faecalis were seeded on different membranes: Memlock (collagen), Memlock Pliable (collagen), Agronaut (collagen), and PermaPro (PTFE); n = 4. After in vitro cultivation for 6days, CAP using a kINPen® MED with an output of 5 W was applied 5min and 10min. Bacterial colony-forming units (CFU) were quantified to detect decontamination effectiveness. In addition, live and dead staining as well as scanning electron microscopy (SEM) of membranes was performed for validation and surface texture analysis. Bacterial colonization was highest on collagen-based membranes (CFU Memlock: 14.38 ± 8.91). The results showed that CAP significantly reduced bacterial colonization on all membrane types after 10min application of CAP; Memlock (CFU after 10min 0.22 ± 0.16^106; p = 0.0256), Argonaut (CFU after 10min 0.02 ± 0.01^106; p = 0.0129) and PermaPro (complete bacterial decontamination; p = 0.0058). This was paralleled by fluorescence and scanning electron microscopy. CAP was most effective on smooth membrane surfaces as SEM revealed. CAP thus offers a non-invasive, cost-effective method to reduce bacterial infections in guided bone regeneration using membranes.

Abstract A020: LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA- sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5- DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as biomarkers in a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel in vitro and in vivo will be conducted, as they could be targeted for improved outcomes in pancreatic cancer patients and assist in the diagnosis of metastatic progression based on RNA-seq data of primary pancreatic tumors or the development of a liquid biopsy. Citation Format: Shivali Singh. LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr A020.

Abstract A035: A real-time PCR method for the detection of cancer-specific methylation patterns in cfDNA

Abstract Non-invasive liquid biopsy tests are proving to be the next frontier in cancer diagnostics with methylation emerging as a reliable biomarker for low levels of circulating tumor DNA (ctDNA). There is a rising interest in sensitive, low-cost liquid biopsy assays to detect low copies of hypermethylated ctDNA in an excess background of non-cancer-associated hypomethylated cell- free DNA (cfDNA). Real-time quantitative methylation-specific PCR (qMSP) allows for the detection of low abundance methylated fragments. qMSP approaches have previously been developed but are predominantly designed to target a specific CpG site. To date we are not aware of any qMSP approaches that target pan-cancer-associated methylation patterns across multiple CpG sites. Harbinger Health has developed a qMSP method with locked nucleic acid (LNA) blockers that target methylation haplotypes, allowing for multiplex enrichment and quantification of cancer-specific methylation patterns. Using targeted bisulfite sequencing, we identified ten pan-cancer-informative CpG-dense regions which showed consistent contiguous elevated methylation states in cancer cfDNA and low levels of methylation in non-cancer cfDNA. We designed qMSP assays for these regions and LNA blockers which bind to unmethylated target CpG sites, outcompeting the hydrolysis probe through a high Tm differential. This prevented non-specific probe hybridization. The qMSP-LNA assays were evaluated in simplex and multiplex using cell line DNA in a titration of hypermethylated “ctDNA” spiked into hypomethylated “cfDNA” to simulate varying ctDNA levels, and then validated with cancer and non-cancer cfDNA samples at 5 ng input, equivalent to 1450 haploid copies. The percentage of methylated DNA was estimated by the ratio of methylated copies (qMSP-LNA) to total copies (internal reference), which were quantified by standard curves. The qMSP-LNA assays detected low abundance methylated DNA fragments down to 23 target copies. LNA blockers completely depleted background signal originating from unmethylated DNA with high specificity, showing no inhibition of methylated DNA detection. When tested in cfDNA samples which varied in conversion efficiency, discordant methylation states, and methylation abundance, the assays reproducibly amplified and detected highly methylated fragments which correspond to cancer signal. Harbinger Health has developed qMSP-LNA assays for contiguous CpG biomarkers which differentiate cancer and non-cancer samples from only ten pan-cancer-informative regions. The qMSP-LNA method detected low abundance fragments with specific methylation patterns with high specificity and sensitivity. The assay reproducibly detected methylated DNA in cfDNA samples that represent a clinically relevant range of methylation signal and will be further validated in a larger cohort of cancer and non-cancer cfDNA samples. Due to the high specificity and sensitivity, this cost-effective PCR method may provide utility and improve access for early cancer detection and monitoring. Citation Format: Emily Neaga, Caitlin Gilley, Sarah Falotico, Mayur Gurnani, Zhenyu Zhang, Jocelyn Charlton, Miguel Williams, Anthony Shuber. A real-time PCR method for the detection of cancer-specific methylation patterns in cfDNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A035.

Saliva NIR spectroscopy and Aquaphotomics: a novel diagnostic approach to Paratuberculosis in dairy cattle

IntroductionParatuberculosis is a granulomatous intestinal infection that affects ruminant animals worldwide. The disease is often detected when most animals are already infected due to the long incubation period and the high transmissibility of the infectious agent. The lack of a comprehensive method to diagnose Paratuberculosis is a global challenge. Therefore, a non-destructive, fast, and cost-effective diagnostic method for early detection of Paratuberculosis is crucial.MethodsNear-infrared spectroscopy (NIRS) and Aquaphotomics have the potential to diagnose the disease by detecting changes in biological fluids. This study aimed to investigate the diagnostic ability of NIRS and Aquaphotomics for Paratuberculosis in dairy cattle by monitoring and data mining of saliva. The diagnostic models were developed according to saliva spectra of dairy cattle in the NIR range and 12 water absorbance bands from 100 to 200 days after calving in two groups: positive and negative, based on the same results of seven ELISA tests of blood plasma, as a reference test.ResultsBoth NIRS and Aquaphotomics methods had high diagnostic accuracy. Using QDA and SVM models, 99% total accuracy, 98% sensitivity, and 100% specificity were achieved in internal validation. The total accuracy in external validation was 90%. This study presents two novel approaches to diagnosing Paratuberculosis in dairy cattle using saliva.DiscussionThe study found that changes in water absorbance spectral patterns of saliva caused by complex physiological changes, such as the amount of antibody related to Paratuberculosis in dairy cattle as biomarkers, are crucial in detecting Paratuberculosis using NIRS and Aquaphotomics.

Evaluation of F1 hybrids against root knot nematode (<i>Meloidogyne incognita</i>) resistance in Brinjal (<i>Solanum melongena</i> L.)

Brinjal is one of the most important commercial solanaceous vegetable crops. Root knot nematodes cause severe yield losses in brinjal both in open and poly house conditions. Host plant resistance is considered to be a viable solution and cost-effective method to manage the root knot nematodes. Ten genotypes along with their nineteen F1 hybrids were screened for resistance to root knot nematode and biochemical basis of resistance was assessed. Two F1 hybrids viz., IIHR-824 x VI046101, IIHR-824 x IIHR-766, parents viz., IIHR-824 and VI046103 were found to be resistance to M. incognita with gall index/ egg mass index of 1. Three F1 hybrids, IIHR-824 x IIHR-356, IIHR-824 x IIHR-835, VI046103 x IIHR-834 showed moderately resistant reaction. The root biochemical compounds analysis indicated that, total phenolic content (67.05 mg/g) and flavonoids (121.32 mg/g) were found higher in the inoculated roots of resistant line i.e. IIHR-824 indicating their role in conferring resistance. The identified F1 hybrids having resistance can be explored for commercial cultivation.

Abstract A067: lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA-sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5-DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as a biomarker panel for a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel are being conducted, in vitro and in vivo, to create a novel liquid biopsy to assist in the prognostic diagnosis of metastatic progression of pancreatic cancer. Citation Format: Shivali Singh. lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A067.

Antimicrobial Peptides: A Promising Alternative to Conventional Antimicrobials for Combating Polymicrobial Biofilms.

Polymicrobial biofilms adhere to surfaces and enhance pathogen resistance to conventional treatments, significantly contributing to chronic infections in the respiratory tract, oral cavity, chronic wounds, and on medical devices. This review examines antimicrobial peptides (AMPs) as a promising alternative to traditional antibiotics for treating biofilm-associated infections. AMPs, which can be produced as part of the innate immune response or synthesized therapeutically, have broad-spectrum antimicrobial activity, often disrupting microbial cell membranes and causing cell death. Many specifically target negatively charged bacterial membranes, unlike host cell membranes. Research shows AMPs effectively inhibit and disrupt polymicrobial biofilms and can enhance conventional antibiotics' efficacy. Preclinical and clinical research is advancing, with animal studies and clinical trials showing promise against multidrug-resistant bacteria and fungi. Numerous patents indicate increasing interest in AMPs. However, challenges such as peptide stability, potential cytotoxicity, and high production costs must be addressed. Ongoing research focuses on optimizing AMP structures, enhancing stability, and developing cost-effective production methods. In summary, AMPs offer a novel approach to combating biofilm-associated infections, with their unique mechanisms and synergistic potential with existing antibiotics positioning them as promising candidates for future treatments.

Abstract 4138494: Remote Blood Pressure Monitoring and Intervention as a better and cost-effective method of Hypertension control compared to Usual care: A Systematic Review

Introduction/Background: Hypertension is a leading cause of morbidity and mortality. Despite treatment recommendations and encouragement of lifestyle changes, the actual rate of blood pressure control is still not at par. Remote intervention methods have been shown to achieve better rates of blood pressure control utilising lesser resources and lower healthcare costs. We conducted a systematic review by qualitatively evaluating the potential impact of remote monitoring and interventions compared to usual care in controlling Hypertension. Research Question: Are remote monitoring techniques and interventions better than usual in-person blood pressure checks for hypertension control? Methods: We did a comprehensive literature search of Pubmed/MEDLINE, Google scholar, Cochrane central Library, PLOS ONE, ScienceDirect and Clinicaltrials.gov to identify eligible randomised control trials and clinical trials published between July 2013 and May 2025. A Risk of Bias assessment was conducted using Cochrane Risk of Bias tools such as ROB-2 for randomised control trials and ROBINS-1 for cohort studies. This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Of the 5,185 records analysed, 10 randomised control trials, 1 cohort study and 1 implementation study satisfied our inclusion criteria. Compared to usual care, remote monitoring methods showed significant difference in systolic blood pressure control at 6-12 months in 9 out of 12 studies, while 3 studies did not show any significant difference. Quality of life, physical health, mental health and drug compliance have also shown a significant positive difference in patients. Remote self monitoring interventions were found to be more cost-effective than usual care. They also reduced the load of patients seeking appointments for hypertension control thereby improving the quality of patient care. Conclusion: The management of clinical hypertension is a challenging entity. Conventional methods of regular in-office blood pressure checks are both tedious and resource consuming. Using remote monitoring methods have shown to significantly improve blood pressure control compared to routine methods. It also eliminates white-coat hypertension during follow-up blood pressure checks which leads to more appropriate interventions. Remote monitoring and intervention for hypertension control is time-effective, cost-effective and improves quality of life.

Agronomic Practices for Management of Ginger Bacterial wilt Disease: A Review

Ginger is one of the most important spices, particularly for small-scale farmers in Ethiopia. However, bacterial wilt is a major constraint to ginger production, and it was reported for the first time in 2012. The disease is caused by the bacteria <i>Ralstonia</i> <i>solanacearum</i>. Common symptoms in infected plants include wilting, stunting, yellowing of foliage, and rhizome rot. The disease is now widespread across all ginger-growing regions worldwide, spreading through soil, water, infected rhizomes, and plant debris. A major challenge in managing bacterial wilt has been the lack of effective control methods. This review primarily focuses on recent advances in control measures, including agronomic and cultural practices such as soil amendment, rhizome treatment, and other cultural practices. Soil and rhizome solarization has proven to be a cost-effective method that is compatible with other pest management tactics. Furthermore, the use of organic matter such as crop residue and animal manure has been investigated as a means of inducing <i>R. solanacearum</i> suppression since it enhances the physical, chemical, and biological characteristics of soil. The application of certain plants and their essential oils as bio-fumigants has also been examined as an alternative approach to managing bacterial wilt as part of an integrated disease management system. Crop rotation, tillage, and field sanitation play vital roles in disease management. Furthermore, other farm practices, such as the use of healthy seeds, cultivation in disease-free areas, cover crops, bio-mulch, and regular field inspection, also contribute to the suppression of this pathogen. Overall, employing agronomic and cultural practices in combination with an integrated disease management strategy offers a promising approach for controlling bacterial wilt and ensuring sustainable ginger production.

Parental Reconstruction from a Half-Sib Population of Stoneless Jujube Ziziphus jujuba Mill. Based on Individual Specific SNP Markers Using Multiplex PCR

The selection of unique and individual-specific SNPs is important as compared with universal SNPs for individual identification. Therefore, the main significance of this research is the selection of specific SNPs in male parent and the identification of offspring with these specific SNPs in their genome by multiplex PCR, which is utilized for genotyping of 332 half-sib plants of Ziziphus jujuba.This cost-effective method makes as much as possible to utilize the same amount of each pair of various targeted loci primers. After PCR amplification of targeted genome parts, the mixed products can be directly used in a next-generation sequencing platform. We concomitantly amplified 10 unique SNP loci at 10 different chromosomes of male JingZao 39 plants in 332 half-sib plants and sequenced them on the Illumina Novaseq 6000 platform. Analysis of SNP genotyping accuracy of 332 half-sib plants showed that all 10 unique SNPs in all 332 plants were correctly amplified in this multiplex PCR method. Furthermore, based on Mendelian inheritance, we identified 124 full-sib plants that have 10 unique SNPs in their genomes. These results were further confirmed by whole genome resequencing of 82 randomly selected half-sib plants, and the identity-by-descent values of all full-sib plants were between 0.4399 to 0.5652. This study displayed a cost-effective multiplex PCR method and proper identification of pollen parent through specific SNPs in half-sib progenies and firstly obtained a full-sib population between ‘Wuhezao’ and ‘JingZao 39’, segregating for stone and stoneless fruit.

Simplifying acquisition of essential diagnostics: A comprehensive costing tool for anatomic pathology.

Histopathology is the core diagnostic tool for cancer in pathology laboratories around the world, but there are disparities in access to diagnostics globally. As recognition of the need for cancer care and treatment grows, especially in the wake of World Health Organization programs for cervical, breast, and pediatric cancers, policymakers and health care funders are seeking tools and processes that allow for the largest number of patients to receive a diagnosis at the lowest cost. As histopathology represents the most cost-effective diagnostic method by sheer number of tumor types and volume, understanding the detailed logistics and costs for histology as well as the impactful benefits of economies of scale (ie, larger volumes are less expensive per patient) and scope (ie, the multiple stains available after basic histology sectioning) is paramount to planning an effective publicly funded or government laboratory. Understanding the economic structure of a country's population along with the financial model of a histology laboratory also leads to a market understanding of private laboratories, which can provide services at a profit as well as pro bono services more cost-effectively than purely public laboratories. We have developed a comprehensive, scalable costing tool of a functioning histology laboratory that accounts for all feasible costs and variations in models of service. The tool allows for a standardized approach to selecting goods needed to provide histology services and serves as a guide for implementation of pathology services. Using the tool, laboratories can achieve self-sustainment and long-term financial health while incorporating a proportion of impoverished patients who cannot afford out-of-pocket expenses.

Assessment of Risk for Immune and Psychiatric Disorders Using qPCR-Based Monitoring of the nan Gene in Gut Microbiota: A Non-invasive Approach

Aim: This study aimed to establish a non-invasive, rapid, and cost-effective method to assess the potential risk of immune and psychiatric disorders by quantifying nan gene levels in gut microbiota, specifically focusing on Ruminococcus gnavus and other Lachnospiraceae species associated with mucin degradation. Methodology: We first designed a primer set targeting the consensus sequence of the nanA gene, which is highly conserved within nan gene clusters. To validate this primer set, we performed Next-Generation Sequencing (NGS) on the PCR-amplified fragments. To explore the association between nan levels and immune or psychiatric disorders, we conducted qPCR to quantify nan levels in the intestines, analyzing intestinal DNA from both allergy-induced mice with or without fructan treatment, and dogs with or without aggressive behavior. Additionally, to assess whether nan levels reflect the clinical status of immune disorders, fecal samples were collected from 45 patients with ulcerative colitis (UC) and analyzed for nan levels. Results: NGS analysis of DNA fragments amplified from various intestinal samples using the nan primer set confirmed the presence of nanA sequences from R. gnavus and other members of the Lachnospiraceae family, including Blautia and Dorea species. The qPCR quantification of nan levels using this primer set revealed that allergy-induced mice treated with fructans, which are known to be associated with lower allergy scores compared to untreated mice, exhibited significantly reduced nan levels. Additionally, the nan levels of aggressive dogs were substantially higher than those of non-aggressive dogs. Notably, nan levels were also substantially elevated in patients with UC in comparison to the healthy control individuals. Conclusion: qPCR-based measurement of nan levels in gut microbiota shows potential for selectively detecting pathogenic nan-harboring strains and may reflect the clinical status of immune and psychiatric disorders. This approach could provide a non-invasive, rapid, and cost-effective method for assessing the risk of these disorders.

Barriers and Strategies for Rotavirus and Cholera Vaccine Uptake: A Systematic Review of Community-based Interventions in Bangladesh, India, and Pakistan

Background: Diarrhea is the second leading cause of death in children and poses a major threat to public health. It is mainly caused by pathogenic organisms of viral, bacterial, or fungal origin, two of which has been preventable via vaccination and has been identified as rotavirus and cholera. In 2020, India, Pakistan, and Bangladesh were among the top 10 South Asian countries with the highest mortality rates from childhood diarrhea. India and Pakistan are further listed by the WHO among the top five countries with the highest recorded mortality among children under five years old. Bangladesh has experienced the highest number of cholera epidemics. Vaccination is recommended as a potent preventive approach against rotavirus and cholera induced diarrhea and is considered the most cost-effective prevention method. However, despite their proven effectiveness, other factors appear to affect the impact of vaccination strategies in these countries. Therefore, this study aimed to explore these nonclinical factors. Methods: This study was conducted as a systematic review which involved the systematic search and selection of qualitative data from primary studies concerning the research topic which was developed using the SPIDER framework. The PRISMA tool was used to carry out this process, and the CASP was used to evaluate the methodological quality of each study. The combined data were then harmonized using meta-synthesis and analyzed thematically. Findings: Four themes emerged from the analysis of the study data: pre-vaccination strategy experience, post-vaccination strategy impact, opportunities for vaccination strategies, and threats to successful implementation of vaccination strategies. This formed the basis of the study discussion and expounded on the impact of vaccine strategies in the selected countries. Conclusion: The results of this study showed that providing the participants with correct information, vaccine education, willingness to learn despite poor knowledge, and access to vaccination are important solutions to the factors that surround the uptake and coverage of cholera and rotavirus vaccines in Bangladesh, India, and Pakistan as critical influencers of the prevalence of childhood diarrhea induced by rotavirus and cholera pathogens, respectively.