E-Journal UMSIDA (Universitas Muhammadiyah Sidoarjo)
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1909 research outputs found
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Nimesulide with Metformin Lowers Inflammatory Markers in Women with PCOS
No full textGeneral Background: Polycystic Ovary Syndrome (PCOS) is a chronic endocrine and metabolic disorder characterized by hyperandrogenism, anovulation, and low-grade systemic inflammation, which contributes to insulin resistance and cardiovascular risk. Specific Background: Metformin, the first-line treatment for PCOS, has known anti-inflammatory properties, but whether its combination with selective COX-2 inhibitors such as nimesulide offers superior anti-inflammatory efficacy remains underexplored. Knowledge Gap: Evidence on adjunctive NSAID therapy targeting inflammation in PCOS is limited, and the combined effects of metformin and nimesulide on key inflammatory biomarkers, interleukin-6 (IL-6) and C-reactive protein (CRP), have not been systematically evaluated. Aims: This study investigated whether adding nimesulide to metformin enhances anti-inflammatory effects in women with PCOS. Results: In a non-randomized controlled study of 100 participants, both treatments significantly reduced IL-6 and CRP; however, combination therapy produced greater CRP reductions (p < 0.001), while IL-6 changes were comparable. Regression analysis identified total cholesterol and free testosterone as independent predictors of residual IL-6 levels (R² = 0.516). Novelty: This study is among the first to demonstrate synergistic anti-inflammatory effects of COX-2 inhibition with metformin in PCOS. Implications: Findings support the integration of metabolic and anti-inflammatory strategies for PCOS management and highlight the need for randomized trials assessing long-term efficacy and safety of adjunctive COX-2 inhibitors.
Highlight:
Combination therapy with nimesulide enhances metformin’s anti-inflammatory effect on CRP.
IL-6 reduction was comparable between metformin alone and combination treatment.
Total cholesterol and free testosterone independently predict residual inflammation.
Keywords: PCOS, Metformin, Nimesulide, Inflammation, C-Reactive Protei
Prevalence and Antibiotic Resistance Patterns of Uropathogens in Patients with Urinary Tract Infections
No full textGeneral Background: Urinary tract infections (UTIs) remain a significant global health concern, frequently complicated by the rise of antimicrobial resistance (AMR) among common uropathogens. Specific Background: In Iraq, increasing rates of multidrug-resistant bacterial strains, particularly Escherichia coli and Klebsiella pneumoniae, have limited therapeutic options and complicated clinical management. Knowledge Gap: Despite numerous studies on global AMR, region-specific data on uropathogen prevalence and susceptibility profiles in northern Iraq remain scarce. Aims: This study aimed to determine the prevalence and antibiotic resistance patterns of bacterial isolates from UTI patients in Mosul, Iraq, to guide empirical treatment and inform antimicrobial stewardship. Results: Among 173 isolates, E. coli (34.7%), K. pneumoniae (23.1%), and Pseudomonas aeruginosa (17.3%) were predominant. The highest susceptibility was observed with Meropenem (95.4%) and Imipenem (92.5%), while Ciprofloxacin resistance reached 42.2%, indicating restricted treatment options. Novelty: The study provides the most recent regional data on uropathogen distribution and resistance trends in Mosul, integrating microbiological surveillance with demographic analysis. Implications: These findings underscore the urgent need for continuous resistance monitoring, rational antibiotic use, and local antimicrobial stewardship programs to curb the spread of resistant uropathogens and improve clinical outcomes.Highlight :
E. coli remains the leading uropathogen in UTIs, followed by K. pneumoniae and P. aeruginosa.
High resistance to Ciprofloxacin (42.2%) indicates limited treatment options.
Regular surveillance of antibiotic resistance is essential for effective therapy and control.
Keywords : Urinary Tract Infection (UTI), Uropathogens, Antibiotic Resistance, Prevalence, Antimicrobial Susceptibilit
Extent of Response of Corn Growth Traits to Potassium and Humic
No full textGeneral Background: Maize (Zea mays L.) is one of the world’s most important cereal crops, serving as a key food, feed, and industrial raw material. In Iraq, maize productivity remains below the global average due to nutrient imbalances and suboptimal fertilization practices. Specific Background: Potassium plays a crucial physiological role in plant growth, yet its availability is limited in many Iraqi soils. Additionally, humic acid, when applied as a foliar spray, enhances nutrient absorption and photosynthetic efficiency. Knowledge Gap: Limited studies have explored the interactive effects of potassium fertilization and foliar-applied humic acid on maize vegetative growth under Iraqi soil conditions. Aims: This study aimed to evaluate the response of maize (cv. 5018) vegetative traits to different levels of potassium (120 and 140 kg ha⁻¹) and humic acid (3 and 4 ml L⁻¹) applied through foliar feeding. Results: The results showed that 120 kg ha⁻¹ potassium significantly enhanced plant height (249.50 cm), stem diameter (2.38 cm), number of leaves (15.64 plant⁻¹), and dry weight (182.94 g). Foliar application of humic acid at 4 ml L⁻¹ further improved stem diameter and leaf number. Novelty: This research highlights the synergistic potential of potassium and humic acid in optimizing maize vegetative performance in potassium-limited soils. Implications: The findings provide a practical basis for refining fertilization strategies to enhance maize productivity in similar agroecological regions.Highlight :
Potassium levels of 120 and 140 kg ha⁻¹ increased plant height and stem diameter.
Humic acid at 3 and 4 ml L⁻¹ improved stem diameter and number of leaves.
Combined potassium and humic treatments enhanced overall vegetative growth.
Keywords : Maize, Potassium, Foliar Feeding, Humic Acid, Growth Trait
Econometric Analysis of the Relationship Between Crop Yields Under Agricultural Risk Diversification
No full textGeneral Background: Agricultural diversification is a vital strategy for reducing systemic risks and stabilizing farm income under climate variability. Specific Background: In Uzbekistan, particularly in the Namangan region, limited empirical evidence exists on how wheat and cotton yields interact within the framework of risk diversification. Knowledge Gap: Despite global studies on crop diversification, the causal and econometric relationships between major crops under local environmental conditions remain underexplored. Aims: This study examines the temporal and econometric interdependence between wheat and cotton yields from 1990 to 2024 using correlation analysis, Granger causality tests, and Vector Autoregression (VAR) modeling. Results: Findings reveal that while most districts exhibit weak or negative correlations conducive to diversification, the Chust district shows a strong positive yield relationship due to similar agronomic conditions. Granger causality indicates that in Kosonsoy and Norin, wheat yield significantly influences cotton yield, whereas in Turaqo‘rg‘on the reverse holds true. Novelty: The study introduces a district-level econometric assessment of inter-crop dynamics, highlighting asymmetric causal patterns shaped by soil and water resource variations. Implications: Results suggest that optimizing crop rotation and water distribution can mitigate covariate risks and stabilize farmers’ income, offering evidence-based guidance for regional agricultural policy in Uzbekistan.Highlight :
The study examines the econometric relationship between wheat and cotton yields under agricultural risk diversification in Namangan region.
Results show varied correlations and causal directions, influenced by soil and water resource conditions.
Findings support policies to enhance crop rotation, resource management, and income stability for farmers.
Keywords : Agricultural Risks, Diversification, Wheat, Cotton, Yiel
Basic Evaluation of Solar Energy Utilization in Gas Pressure Reduction Stations for Fuel Consumption Reduction
No full textGeneral Background: Natural gas pressure reduction stations (PRS) consume fuel for gas preheating, causing CO₂ emissions. Specific Background: The Joule-Thomson effect cools gas during throttling, requiring continuous heating to prevent hydrates. Knowledge Gap: Few studies assess solar-assisted PRS performance under real conditions. Aims: This study evaluates parabolic trough collectors (PTCs) with thermal storage for preheating in PRS. Results: The system saves 40% fuel (256,000 m³/year), reduces CO₂ by 14,000 tons, and achieves 11.5% IRR with a 4.5-year payback. Novelty: It integrates validated transient modeling for practical scalability. Implications: Solar thermal integration provides an effective strategy to decarbonize gas infrastructure and enhance energy efficiency.
Solar thermal integration in pressure reduction stations achieves 40% fuel savings and significant CO₂ emission reduction.
The system shows strong economic performance with an IRR of 11.5% and a 4.5-year payback period.
The approach supports sustainable and scalable solutions for gas infrastructure decarbonization.
Keywords : Solar thermal energy, Natural gas pressure reduction, Fuel consumption reduction, Exergy analysis, CO₂ emission
Innovative Model for Developing the Service System in the Agro-Industrial Complex Based on Clustering Principles
No full textGeneral Background: The agro-industrial complex serves as a cornerstone of national economic stability, integrating agricultural production, processing, and distribution systems that ensure food security and rural development. Specific Background: Rapid globalization, technological change, and increasing competitiveness have revealed the inefficiency of conventional service infrastructures in agro-industrial systems, particularly in resource utilization, innovation adoption, and coordination among stakeholders. Knowledge Gap: Despite the global emphasis on clustering as a driver of competitiveness, there remains limited empirical and methodological understanding of how cluster-based service models can optimize performance through digital and economic integration in emerging economies such as Uzbekistan. Aims: This study aims to develop an innovative cluster-based model for agro-industrial service systems that enhances efficiency, technological independence, and competitiveness through mathematical modeling and digital monitoring tools. Results: The proposed model integrates key indicators—including technical independence, infrastructure competitiveness, socio-economic stability, and export potential—into a unified efficiency index supported by regression-based analysis. The findings demonstrate that implementing a Public-Private Partnership (PPP)-driven cluster framework enables balanced investment distribution, improved financial flow management, and enhanced innovation performance across the agro-industrial value chain. Novelty: The study introduces a digitally enabled cluster model governed by Key Performance Indicators (KPIs) and data analytics, providing a new paradigm for evaluating and optimizing service systems in agro-industrial networks. Implications: The model offers a replicable framework for policymakers and practitioners to foster sustainable agro-industrial development, enhance investment attractiveness, and strengthen economic resilience in developing regions.
Highlights:
Introduces a cluster-based digital model to enhance agro-industrial efficiency.
Develops a unified efficiency index integrating key economic and technical indicators.
Promotes PPP-driven collaboration for sustainable and competitive agro-industrial growth.
Keywords: Agro-industrial Cluster, Innovation, Competitiveness, Digital Model, Sustainabilit
Association Between Claudin-5 And Angulin-1 In Alzheimer's Disease
No full textGeneral Background: Alzheimer’s disease is a progressive neurodegenerative disorder in which cognitive decline is closely linked to blood–brain barrier dysfunction. Specific Background: Tight-junction proteins such as Claudin-5 and Angulin-1 play key roles in maintaining barrier integrity, yet their involvement in Alzheimer’s pathology remains insufficiently clarified, and evidence on associated micronutrient alterations is still limited. Knowledge Gap: Despite emerging data suggesting barrier disruption and B-vitamin deficiencies in Alzheimer’s disease, the combined diagnostic relevance of Claudin-5, Angulin-1, and vitamins B9 and B12 has not been systematically examined. Aims: This study investigates the relationship between Claudin-5 and Angulin-1 in Alzheimer’s disease and evaluates differences in serum vitamin B9 and B12 levels between affected individuals and healthy controls. Results: Serum analyses revealed significantly reduced Angulin-1, Claudin-5, vitamin B9, and vitamin B12 levels in Alzheimer’s patients, alongside marked alterations in lipid profiles. ROC analysis demonstrated exceptionally high diagnostic performance for all measured biomarkers. Novelty: This work provides integrated biochemical evidence linking tight-junction protein depletion with B-vitamin deficiencies in Alzheimer’s disease, suggesting a coordinated disruption of vascular and metabolic pathways. Implications: The identified biomarkers show strong potential for non-invasive diagnostic applications and may guide the development of therapeutic strategies aimed at restoring barrier integrity and micronutrient balance.Highlight :
Claudin-5 and Angulin-1 show significant reductions in Alzheimer’s patients, reflecting impaired tight-junction function in the blood–brain barrier.
Vitamin B9 and B12 levels are markedly lower in Alzheimer’s patients than in healthy controls, indicating an important metabolic alteration.
All biomarkers demonstrate high diagnostic performance, with strong sensitivity and specificity based on ROC analysis.
Keywords : Claudin-5, Angulin-1, Alzheimer’s disease, Vitamin B9, Vitamin B1
From Shamanic Fraud to Serial Murder: Reconstructing Criminal Liability and Causation in an Indonesian Case Study: Dari Penipuan Shamanik hingga Pembunuhan Berantai: Rekonstruksi Tanggung Jawab Pidana dan Kausalitas dalam Studi Kasus Indonesia
No full textGeneral Background: Fraudulent shamanic practices exploiting beliefs in supernatural money-doubling persist in Indonesia and have escalated into serious violent crimes. Specific Background: The Banjarnegara serial murder case involving a money-doubling shaman revealed a systematic pattern in which fraud preceded and motivated twelve premeditated killings, adjudicated under District Court Decision No. 63/Pid.B/2023/PN Bnr. Knowledge Gap: Prior studies rarely examine the integrated construction of criminal liability combining fraud, premeditated murder, participation, and concursus realis, particularly in comparison with the preventive framework of the new Criminal Code. Aims: This study analyzes the layered application of criminal provisions under the old Criminal Code and compares them with the new Criminal Code to assess proportional accountability and sanctions. Results: The findings show that fraud under Article 378 functioned as the proxima causa triggering premeditated murder under Article 340, aggravated by participation (Article 55) and multiple offenses (Article 65), justifying the imposition of the death penalty despite the introduction of Article 252 of Law No. 1 of 2023. Novelty: The study conceptualizes fraud as a causal foundation for serial premeditated murder within a concursus realis framework. Implications: These findings reinforce the need for integrated repressive and preventive criminal policies to address extraordinary crimes rooted in deceptive supernatural claims.
Highlights:
Fraud functions as the causal trigger for systematic premeditated murder.
Layered application of criminal provisions strengthens proportional accountability.
Preventive norms in the new Criminal Code remain insufficient for extraordinary crimes.
Keywords: Criminal Liability, Premeditated Murder, Fraudulent Shamanism, Concursus Realis, Death Penalt
AI-Driven Genomic Modeling for Predicting Biological Responses to Environmental Pollution
No full textGeneral Background: Environmental pollution from heavy metals and organic contaminants has escalated globally, generating complex biological disruptions across molecular, cellular, and ecological levels. Specific Background: Advances in high-throughput sequencing and multi-omics technologies have revealed that pollutants induce genomic and epigenetic alterations, yet interpreting these multidimensional datasets remains challenging. Knowledge Gap: Existing studies lack integrated analytical frameworks capable of linking pollutant exposure with genome-wide molecular responses in a precise and predictive manner. Aims: This review synthesizes current evidence on pollutant-induced molecular changes and evaluates the potential of artificial intelligence (AI) to model and predict biological responses. Results: Recent applications of machine learning—such as Random Forests, Support Vector Machines, and Convolutional Neural Networks—demonstrate strong performance in identifying key genetic markers, forecasting epigenetic modifications, and estimating organismal vulnerability before clinical symptoms appear. Novelty: This article highlights the emerging role of AI-driven genomic modeling as a transformative approach that integrates environmental and genomic datasets to capture multilevel biological responses with high accuracy. Implications: The integration of AI with genomics offers a proactive strategy for early detection of pollution-induced molecular changes, enhances environmental risk assessment, and informs targeted remediation, biodiversity protection, and long-term ecosystem management.Highlight :
Environmental pollutants cause DNA methylation changes, histone modifications, and disruptions in cellular defense mechanisms.
Machine learning algorithms predict epigenetic changes and identify genetic markers before physiological symptoms manifest.
AI integration enables early pollution detection, bioremediation support, and proactive ecosystem management.
Keywords : Environmental Pollution, Artificial Intelligence, Environmental Genomics, Epigenetic Change, Predictive Modelin
Green Marketing, Greenwashing, and Premium Pricing Effects on Agrochemical Sales Performance: Pengaruh Green Marketing, Greenwashing, dan Penetapan Harga Premium terhadap Kinerja Penjualan Agrokimia
No full textGeneral Background: The agrochemical industry faces growing public scrutiny as sustainability concerns and environmental risks of synthetic chemicals intensify, prompting firms to integrate sustainability-oriented strategies into their business models. Specific Background: In Indonesia, agrochemical companies increasingly rely on green marketing communication, sustainability claims, and premium pricing to position green chemical products amid regulatory pressure and rising environmental awareness. Knowledge Gap: Empirical evidence remains limited regarding how green marketing, greenwashing practices, and premium pricing are simultaneously associated with sales performance in the agrochemical sector, particularly from the perspective of marketing practitioners. Aims: This study examines the relationships between green marketing strategies, greenwashing practices, and premium pricing with the sales performance of green chemical products, while assessing the moderating role of premium pricing. Results: Quantitative analysis using regression and moderated regression analysis indicates that green marketing, greenwashing, and premium pricing are each positively and significantly associated with sales performance, whereas premium pricing does not significantly moderate the relationships between green marketing or greenwashing and sales performance. Novelty: The study demonstrates that, within the Indonesian agrochemical context, greenwashing practices can be associated with short-term sales performance alongside green marketing and premium pricing. Implications: The findings suggest that agrochemical firms should prioritize credible and transparent sustainability communication and apply value-based pricing, as sales performance is driven by direct strategic signals rather than interaction effects among sustainability marketing and pricing strategies.
Highlights:
Sustainability-oriented communication shows a positive association with product sales outcomes.
Short-term market gains are observed alongside unverified environmental claims.
Price positioning serves as a direct market signal rather than an interaction mechanism.
Keywords: Green Marketing, Greenwashing, Premium Pricing, Sales Performance, Agrochemical Industry