Systemic Risk Research Articles

A historical analysis of the banking system and its impact on Greek economy

This paper outlines the critical role of banks in the Greek economy, emphasizing their importance for maintaining stability and fostering financial growth. It traces the historical development of the Greek banking system, examines its current structure, and explores future challenges and opportunities. The paper adopts a historical-analytical approach, beginning with a comprehensive review of the Greek banking system’s evolution. It then delves into four key pillars, regulation, function, accessibility, and societal impact, to provide an in-depth analysis of the banking sector. This method allows for a well-rounded understanding of both the historical context and the current dynamics influencing the Greek financial landscape. The Greek banking system has been a pivotal player in the country’s economic development, especially during periods of recovery and growth. Post-2008, the global financial crisis exposed significant weaknesses in the banking sector, including a prevailing deficit of confidence. Regulatory reforms, while effective in some areas, have left challenges related to accessibility, societal trust, and economic resilience. The need for further reforms, especially in digital banking and transparency, is identified as crucial for long-term stability and growth. Conclusion: Greek banks remain essential to the national economy, yet they face considerable challenges, especially regarding public confidence and systemic risks. Addressing these issues through targeted reforms is vital for creating a more resilient and sustainable future for the Greek banking sector. The paper provides actionable recommendations for policymakers, emphasizing the importance of strengthening regulatory frameworks, enhancing accessibility to financial services, and fostering societal trust through improved transparency. The recommendations aim to help the Greek banking sector navigate future uncertainties while supporting economic growth.

Leveraging High-Throughput Analytics and Automation to Rapidly Develop High-Concentration mAb Formulations: Integrated Excipient Compatibility and Viscosity Screening

Abstract Background Formulation screening is essential to experimentally balance stability and viscosity in high-concentration mAb formulations. We developed a high-throughput approach with automated sample preparation and analytical workflows to enable the integrated assessment of excipient compatibility and viscosity of mAb formulations. Methods Ninety-six formulations of a trastuzumab biosimilar were screened by combining 8 types of excipient modifiers with 4 types of buffers across a pH range of 4.5 to 7.5. Key stability risks, including high molecular weight (HMW) aggregation and fragmentation, were thoroughly assessed along with viscosity at high concentrations. Additionally, several biophysical parameters were evaluated for their ability to predict stability or viscosity outcomes. Multiple linear regression was applied to fit the data and identify key factors. Results The optimal pH range for the trastuzumab biosimilar was found to be 5.0 to 6.5, based on opposing pH dependencies for stability and viscosity. Buffer type had a minor effect on viscosity and fragmentation but played a significant role in influencing HMW aggregates, with Na-acetate and histidine-HCl being the best candidates. The impact of excipient modifiers on viscosity, HMW, and fragmentation depended on both pH and buffer type, showing strong interactions among factors. Arginine-HCl and lysine-HCl effectively lowered viscosity of the trastuzumab biosimilar at pH levels above 6.0, while glycine formulations were more effective at reducing viscosity below pH 6.0. Histidine-HCl, arginine-HCl, and lysine-HCl lowered the risk of HMW aggregation, whereas formulations containing Na-phosphate or NaCl showed higher HMW aggregation. Formulations with arginine-HCl, lysine-HCl, and NaCl demonstrated a rapid increase in fragmentation at pH levels below 5.0, while Na-aspartate formulations showed increased fragmentation at pH levels above 6.5. Conclusion Hence, it is important to optimize the levels of each chosen excipient in the formulation study to balance their benefits against potential incompatibilities. This study serves as a foundation for identifying high-concentration antibody formulations using a high-throughput approach, where minimal materials are required, and optimized formulation design spaces can be quickly identified.

Online Investor Sentiment via Machine Learning

In this paper, we propose utilizing machine learning methods to determine the expected aggregated stock market risk premium based on online investor sentiment and employing the multifold forward-validation method to select the relevant hyperparameters. Our empirical studies provide strong evidence that some machine learning methods, such as extreme gradient boosting or random forest, show significant predictive ability in terms of their out-of-sample performances with high-dimensional investor sentiment proxies. They also outperform the traditional linear models, which shows a possible unobserved nonlinear relationship between online investor sentiment and risk premium. Moreover, this predictability based on online investor sentiment has a better economic value, so it improves portfolio performance for investors who need to decide the optimal asset allocation in terms of the certainty equivalent return gain and the Sharpe ratio.

The Application of Fintech (Financial Technology) and Risk Management

This paper provides a comprehensive overview of the impact and applications of financial technology (Fintech) across various sectors such as payment and clearing, lending, wealth management, insurance, and risk management. It highlights the transformative potential of Fintech in enhancing financial efficiency, inclusiveness, and risk management through the utilization of modern technologies like big data, artificial intelligence, and blockchain. The paper delves into specific examples such as online payment systems, peer-to-peer lending platforms, robo-advisory services, and blockchain technology. Furthermore, it discusses the challenges and risks associated with Fintech, including regulatory issues, security concerns, and the need for effective risk management practices. The abstract emphasizes the importance of responsible risk management in ensuring financial stability and preventing systemic risks in the Fintech sector. Overall, the abstract provides a comprehensive understanding of the role of Fintech in shaping the future of the financial industry and emphasizes the need for effective regulation, risk management, and technological innovation to harness its full potential while mitigating associated risks.

Risk management and corporate ESG performance: The mediating effect of financial performance

This study utilizes a sample of A-share manufacturing companies listed in China from 2012 to 2022 to explore the intricate interplay between systemic risk, financial performance, and ESG (Environmental, Social, and Governance) performance. The findings reveal that a decrease in systemic risk positively influences corporate ESG performance with a notable lag of 1–2 periods, with financial performance serving as a pivotal mediator in this dynamic. However, within the heavy pollution industry, the enhancement of ESG performance through systemic risk reduction is observed to be comparatively muted.

Mechanistic insight into interactive effect of microplastics and arsenic on growth of rice (Oryza sativa L.) and soil health indicators

Microplastics (MPs) pollution has recently become a major concern for agroecosystems. The interplay between MPs, and heavy metal(loid)s in the soil can intensify the risks to plant growth and human health. The current study investigated the interactive effects of arsenic (As) and biodegradable and petroleum-based conventional MPs on rice growth, As bioavailability, soil bacterial communities, and soil enzyme activities. As-contaminated soil (5 mg kg−1) was treated with conventional MPs i.e., polystyrene (PS) and polyethylene (PE) and biodegradable MPs i.e., polylactic acid (PLA) and polybutylene adipate terephthalate (PBAT) at 0.1 % and 1 % rates. In a pot experiment, rice plants were cultivated in soil co-contaminated with As and MPs. PLA-MPs exhibited significant interactions with As, increasing its bioavailability and impairing rice plant growth by enhancing plant oxidative stress. The results illustrated that T2 treatment (PLA-MPs @ 1 % + As 5 mg kg−1) significantly decreased the root and shoot lengths, root and shoot dry weights as well as the rates of photosynthesis, transpiration, intercellular CO2, and stomatal conductance in rice plants. Biodegradable PLA-MPs @ 1 % resulted in increased uptake of As in rice roots, stems, and leaves by 13.4 %, 38.9 %, and 20.6 %, respectively. In contrast, conventional PE-MPs @ 1 % showed contradictory results with As uptake declined by 2.2 %, 5.1 %, and 9.9 % in rice roots, stem and leaves. Soil enzyme kinetics showed that biodegradable MPs increased the activities of soil catalase, dehydrogenase, and phytase enzymes, whereas both conventional PS and PE-MPs decreased their activities. Moreover, As and PLA-MPs combined stress altered soil bacterial communities by increasing the relative abundance of Protobacteria, Acidobacteria, Chloroflexi, and Firmicutes phyla by 49 %, 29 %, 82 %, and 57 %, respectively. This study provides new insights into MPs-As interactions in soil-plant system and ecological risks associated with their coexistence.

A Comprehensive Framework for Machine Learning-Based Threat Intelligence in Health Information Systems

This research work provides a comprehensive architecture of Machine Learning based threat intelligence particularly for Health Information System (HIS). The number of cybersecurity threats executed by healthcare companies is even higher since healthcare organizations continue to introduce digitized data into medical data. This work employs complex machine learning techniques from the MIMIC-III Critical Care Database to develop a practical threat identification and mitigation system. In this case, the strategy of analysis involves selection of data, data processing, modeling and real time dangers identification considering both supervised and unsupervised learning. The results reveal that the proposed framework covers high performance indicators such as: accuracy that equals 97.92%, and the level of precision and recall which also equal 90% ROC AUC has reached 0.94. These results demonstrate that the framework can identify and categorise cybersecurity risks in systems of health information on a regular basis. It not only increases threat perception but also makes the system internally valuable for healthcare IT professionals since it contains real-time monitoring and anomaly detection functionality. Therefore, this study stands in support of the ongoing efforts to enhance the security of the healthcare bodies on the use of policies on cybersecurity so as to ensure the protection of individual patient’s information against new forms of threats.

GeriNOT in the Surgical Inpatient Setting.

The guideline of the Federal Joint Committee (G-BA) on quality assessment measures for the care of patients with hip fracture makes it mandatory for hospitals to use an appropriate geriatric screening instrument in the context of acute inpatient care. After systematic application of GeriNOT and data collection in the admission process with integration into the Hospital Information System (HIS), it is possible to identify potential risks in geriatric patients with other diagnoses as well.With the integration of GeriNOT into the acute inpatient admission process, it was examined whether vulnerable geriatric patients with other diagnoses could benefit from the early initiation of risk identification.The data base for the present study was a retrospective bicentric collection of electronic case records (May 2014 to April 2015, n=3,443). From this primary data set, the subgroup of inpatient acute admissions (n=821) in the orthopaedic/trauma surgery of a study centre was analysed and evaluated with respect to the endpoints "utilisation of needs-based post-inpatient care services" and "new admission to inpatient permanent/short-term care". The predictive power and classification accuracy of GeriNOT of these patients who were 70 years and older to the endpoints were assessed for several groups: total acute admissions, total fractures, hip fracture, and spinal disorders including spinal fractures.A total of 821 patients were admitted as acute inpatients during the study period. The mean age of the patients was 81.4±6.8 years (n=821; 68.1% women, 31.9% men). The following subgroups were formed and analysed: total fractures (n=490), spinal disorders (n=265) including spinal fractures (n=174), and hip fracture (n=108). Both in the overall group (n=821; M=4.279; SD=2.180) and in the subgroups, the mean GeriNOT score was above the threshold ≥4. The highest score was found in the hip fracture group (M=4.852; SD=2.022), and the lowest in the spine fracture group (M=4.177; SD=2.171). At admission, if the terms of variables for requiring treatment were "polypharmacy" and "nursing services already used as needed", there were only slight differences in the diagnostic groups. Admissions from short-term and long-term care occurred in the total group in 16.44% of cases, most frequently with 31.48% in the group of hip fractures, compared to spinal diseases with 6.79%. For this group, GeriNOT detected an elevated risk with respect to the defined endpoints. However, only 4.26% of all patients with identified geriatric risk potential received further geriatric care.The results showed increased geriatric risk in all analysed groups, but most pronouncedly within the group of spinal diseases. The HIS-supported use of GeriNOT offers the possibility of systematic risk identification in acute inpatient admission management. The continuous visualisation of results at HIS workstations throughout the workflow could be used as a starting point for the subsequent application of standardized assessment tools and risk-adjusted treatment pathways. These findings could potentially improve outcomes.

Influence of macroeconomic factors on construction costs: an analysis of project cases

This study explores the relationship between price increase and project cost increase under macroeconomic shocks by considering the hierarchical structure within price categories, diversification of the cost breakdown structure, infrastructure sector, delivery system, construction methods, and type of bid. The analysis of a large construction company with five large projects as embedded units of analysis reveals significant variations in the relative influence of specific factors across the projects. Unit price categories located higher in the hierarchical breakdown structure display lower vulnerability to macroeconomic changes due to their unique and group-specific influencing factors while price categories influenced by macroeconomic factors depart at lower values in the hierarchical structure. Projects with low-cost breakdown structure diversification can either mitigate or exacerbate cost increases depending on construction methods (off-site or on-site), price drivers of most representative materials (global or local), and delivery systems risk allocation. Under macroeconomic crisis periods, public entities may consider giving high priority to projects more reliant on materials driven by regional dynamics (e.g., concrete pouring) over those driven by global market conditions (e.g., steel, aluminum) while prioritizing integrated delivery systems (e.g., design-build) that promote enhanced collaboration, proactive risk management, aligned incentives, and adaptability for managing complexities and volatilities. Complementary, for projects with higher reliance on global market-driven materials, the results suggest that contractors should prioritize early procurement and acquisition of highly volatile resources in projects under macroeconomic crises.

AOP Report: Development of an adverse outcome pathway for deposition of energy leading to bone loss.

Bone loss, commonly seen in osteoporosis, is a condition that entails a progressive decline of bone mineral density and microarchitecture, often seen in post-menopausal women. Bone loss has also been widely reported in astronauts exposed to a plethora of stressors and in patients with osteoporosis following radiotherapy for cancer. Studies on mechanisms are well documented but the causal connectivity of events to bone loss development remains incompletely understood. Herein, the adverse outcome pathway (AOP) framework was used to organize data and develop a qualitative AOP beginning from deposition of energy (the molecular initiating event) to bone loss (the adverse outcome). This qualitative AOP was developed in collaboration with bone loss research experts to aggregate relevant findings, supporting ongoing efforts to understand and mitigate human system risks associated with radiation exposures. A literature review was conducted to compile and evaluate the state of knowledge based on the modified Bradford Hill criteria. Following review of 2029 studies, an empirically supported AOP was developed, showing the progression to bone loss through many factors affecting the activities of bone-forming osteoblasts and bone-resorbing osteoclasts. The structural, functional, and quantitative basis of each proposed relationship was defined, for inference of causal changes between key events. Current knowledge and its gaps relating to dose-, time- and incidence-concordance across the key events were identified, as well as modulating factors that influence linkages. The new priorities for research informed by the AOP highlight areas for improvement to enable development of a quantitative AOP used to support risk assessment strategies for space travel or cancer radiotherapy.

Impact of economic policy uncertainty on systemic risk of real enterprises: Evidence from China

This work examines the impact of economic policy uncertainty on the systemic risk of Chinese real firms from the perspectives of financing constraints and external guarantees. The findings suggest that economic policy uncertainty significantly enhances the systemic risk of real firms. The mechanism test shows that economic policy uncertainty will enhance the level of systemic risk of enterprises by exacerbating their financing constraints and expanding the scale of external guarantees. Heterogeneity analysis shows that the negative impact of economic policy uncertainty on systemic risk is more obvious in enterprises with investment and financing maturity mismatches and poorer corporate governance.

Endogenous Risk Exposure and Systemic Instability

Most research on systemic stability assumes an economy where banks are subject to exogenous shocks. However, in practice, banks choose their exposure to risk. I show that there exists a network risk-taking externality: the risk exposure choices made by connected banks are strategically complementary. Banks within financial networks, especially densely connected ones, become endogenously exposed to excessive risks. The theory offers several novel perspectives on policy debates. For instance, it suggests that limiting government bailouts to interbank exposures can effectively reduce endogenous systemic risk. This paper was accepted by Kay Giesecke, finance. Funding: This work was financially supported by the USC Dornsife Institute for New Economic Thinking Fellowship, the Marshall PhD Fellowship, and European Finance Association Doctoral Tutorial Best Paper Prize. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.01519 .

Prophylactic Cranial Irradiation prior to HCT for Acute Lymphoblastic Leukemia: To Boost or Not To Boost.

Total body irradiation (TBI) with or without cranial radiation boost (CRB) is an integral component of conditioning prior to allogeneic hematopoietic cell transplantation (allo-HCT) in acute lymphoblastic leukemia (ALL). The benefit of CRB is not yet established. This is a retrospective single center cohort study. Between January of 2003 and April of 2019, electronic medical records of 166 patients with ALL were retrospectively reviewed. One hundred forty-three patients with ALL and no prior central nervous system (CNS) involvement were included. Patients were divided into two cohorts according to cranial radiation boost (cohort-1: CNS-/CRB+ (110/143, 77%) and cohort-2: CNS-/CRB- (n=33/143; 23%). No patients received post-transplant prophylactic intrathecal chemotherapy. Following alloHCT, 15 patients (10.5%) experienced relapse; 11 relapses (10%) in cohort-1, and 4 (12%) in cohort-2. Four patients (26.6%) experienced systemic medullary relapse with initial central nervous system (CNS) involvement. One patient (6.6%) experienced isolated first central nervous system relapse after allotransplant with no difference between the two cohorts (6.6% vs 0; P-0.59). Age at transplant and phenotypic subtype were predictive of first central nervous system relapse after allotransplant with respective P-values of 0.001 and 0.015.At a median follow-up of 30 months (range: 2.5-128 months), the estimated 3-year overall survival was 61% (95% CI: 53-69), relapse free survival was 60% (95% CI: 52-69) and 3-year central nervous system-relapse-free survival was 99% and 100% in in cohort-1 and cohort-2 respectively, when systemic relapses were censored. There was no statistical significant difference in either survival or relapse free survival between the two cohorts (P > 0.69). Our results suggest that augmenting total body irradiation with cranial radiation boost in patients with ALL with no prior CNS involvement did not improve relapse risk in central nervous system or survival outcomes.

The need for a risk management framework for data science projects: a systematic literature review

Many data science endeavors encounter failure, surfacing at any project phase. Even after successful deployments, data science projects grapple with ethical dilemmas, such as bias and discrimination. Current project management methodologies prioritize efficiency and cost savings over risk management. The methodologies largely overlook the diverse risks of sociotechnical systems and risk articulation inherent in data science lifecycles. Conversely, while the established risk management framework (RMF) by NIST and McKinsey aims to manage AI risks, there is a heavy reliance on normative definitions of risk, neglecting the multifaceted subjectivities of data science project failures. This paper reports on a systematic literature review that identifies three main themes: Big Data Execution Issues, Demand for a Risk Management Framework tailored for Large-Scale Data Science Projects, and the need for a General Risk Management Framework for all Data Science Endeavors. Another overarching focus is on how risk is articulated by the institution and the practitioners. The paper discusses a novel and adaptive data science risk management framework – “DS EthiCo RMF” – which merges project management, ethics, and risk management for diverse data science projects into one holistic framework. This agile risk management framework DS EthiCo RMF can bridge the current divide between normative risk standards and the multitude of data science requirements, offering a human-centric method to navigate the intertwined sociotechnical risks of failure in data science projects.

How Government Subsidies Facilitate the Digital Transformation of Suppliers

Digital transformation is increasingly recognized as a key driver of sustainable development, enabling suppliers to improve efficiency, reduce resource consumption, and adapt to changing market demands. However, it remains a challenging process for suppliers, often hindered by resource and capacity constraints. This study investigates how government subsidies can facilitate supplier digital transformation, considering supply chain diffusion and local government competition dynamics. Using data from A-share listed companies in China between 2010 and 2021, our analysis reveals that government subsidies significantly promote supplier digital transformation by encouraging a more diversified downstream customer base. Moreover, customer digital transformation can facilitate supplier digital transformation, but spillover effects are higher within the same jurisdiction than across different jurisdictions. This study further identifies that the impact of government subsidies is more pronounced under higher opportunistic risk but is constrained by systemic risk. Additionally, suppliers with higher human capital and a smaller digital divide with customers exhibit greater effectiveness in adopting innovation diffusion. These findings provide valuable insights into optimizing local government subsidies policies to enhance supplier digital transformation and contribute to the broader goal of sustainable development.

6903 The Treatment May Be Worse Than The Disease: The Real-World Clinical Burden Of Disease And Treatment In Congenital Adrenal Hyperplasia

Abstract Disclosure: W. Huang: Consulting Fee; Self; Spruce Biosciences. Research Investigator; Self; Spruce Biosciences. R. Charlton: Employee; Self; Spruce Biosciences. S. Sile: Employee; Self; Spruce Biosciences. C. Dieyi: Employee; Self; STATinMED. S. Adams: Employee; Self; STATinMED. J. Maynard: Employee; Self; STATinMED. C.N. Barnes: Employee; Self; Spruce Biosciences. A.H. Hamrahian: Consulting Fee; Self; Spruce Biosciences. Research Investigator; Self; Spruce Biosciences. Background and Aims: Classic congenital adrenal hyperplasia (CAH) is a group of autosomal recessive conditions that affects the production of adrenal hormones, leading to deficiencies in cortisol and aldosterone, and excess in adrenal androgens. Current treatment includes mineralocorticoids and oral glucocorticoids (GCs) for physiologic cortisol replacement and hypothalamic-pituitary-adrenal (HPA) axis suppression to control androgen levels. The health impacts of hyperandrogenemia include accelerated skeletal maturation leading to adult short stature, precocious puberty, acne, hirsutism, male pattern baldness, adrenal rest tumors, and infertility. There are also serious adverse events due to the long-term use of supraphysiologic doses of GCs. The aim of this study was to explore the risks associated with CAH diagnosis and treatment. Methods: This cross-sectional study used medical administrative claims data within 2014-2021 from RWD Insights®, an all-payer claims database in the US. Adult patients were required to have a diagnosis of CAH (ICD-9/10-CM: 255.9, E25.0, E25.9) and continuous use of oral GCs (defined as a proportion of days covered of 75% or more in any given calendar year). Patients were further required to receive an average daily GC dose of ≥10mg/day hydrocortisone equivalent and be free of pituitary disorders. Non-CAH controls were also selected if they did not have a CAH diagnosis or any GC use. Demographic characteristics and comorbidity rates were compared between patients with and without CAH during the study period. For comorbidity rate comparisons, rate ratios (RR) and 95% confidence intervals (CI) were computed. Results: A total of 1,532,141 (CAH: 2,033; Non-CAH: 1,530,108) were eligible for the study. A lower proportion of the CAH cohort was elderly (i.e., 65+ years; 11% vs. 26%), and there were more females (67% vs. 57%), as compared to the non-CAH cohort. After propensity score matching (PSM) on demographic characteristics, there were 2,019 and 8,076 patients in the CAH and non-CAH cohort, respectively, and patient characteristics were balanced. There were higher rates of comorbidities in the CAH cohort. Some notable differences, RR (95%CI), include GC related comorbidities such as osteoporosis/necrosis, 3.48 (3.36, 3.60) and fractures, 2.14 (1.90, 2.39); metabolic disorders, 2.20 (2.08, 2.33), obesity, 1.35 (1.26-1.44), type 2 diabetes, 1.27 (1.18,1.36), and cardiovascular disorders, 1.24 (1.16, 1.33); and CAH related comorbidities, hirsutism, 11.70 (11.34, 12.06) and testicular hypofunction, 5.48 (5.24, 5.71). Conclusions: This study suggests the association of several comorbidities with CAH, highlighting the burden of both the disease and treatment. Novel, non-steroidal treatments that improve hormonal balance in CAH could ameliorate the systemic risks associated with hyperandrogenemia and chronic overexposure to GCs. Presentation: 6/1/2024

Multiscale dynamic interdependency between China’s crude oil futures and petrochemical-related commodity futures: An integrated perspective from the industry chain system

This paper examines the coupling of China’s petrochemical-related commodity futures from the perspective of an integrated system as well as the multiscale interdependency between this system and Shanghai crude oil futures (SCM) with two globally influential benchmarks, i.e., Brent and WTI, as comparisons. Our methods innovatively build on the multifractal theory and provide in-depth analysis across various time scales. The results show the dynamic coupling of China’s oil industry chain system (ICS) can reflect its level of systemic risk concentration well. The greater the time scale, the stronger the coupling. The abrupt deterioration of the external economic environment enhanced the impact of crude oil on the ICS, but the impact from SCM increased the most. Furthermore, the higher dependency preference of ICS for SCM confirms the effectiveness of this emerging futures market in reflecting domestic oil supply and demand but continuously weakens as the time scale increases, indicating the dominance of Brent and WTI in the long run.

Trade risk transmission of global cobalt industrial chain based on multi-layer network

In order to study the potential systemic risk transmission in cobalt trade, this paper combined the infectious disease model with complex networks to build a multi-layer network trade risk transmission model for cobalt trade based on the transmission of export restrictions and bilateral friction in a single country, in order to simulate the degree of impact of risk transmission in cobalt industry chain, identify key countries and risk transmission paths. The results show that multi-layer network risk transmission of global cobalt trade based on two communication forms has the characteristics of “robust and fragile”. In addition, the risk transmission situation based on bilateral frictions is mainly transmitted by core countries and direct contacts. The risk transmission based on the export restriction of a single country is mainly through direct contact, indirect contact and regional transmission. We also find that the multi-layer trade network of global cobalt trade can resist the bilateral frictional transmission mode better than the transmission mode of single country export restriction. The results can support policy makers to optimize the cobalt trade structure and mitigate the negative impact of trade disruptions.

Testosterone and 5 Alpha Reductase Inhibitor (5ARI) in Benign Prostatic Hyperplasia (BPH): A historical perspective

This paper provides a review of the historical and scientific evolution of testosterone and 5ARI research. It chronicles the evolution from early empirical practices like castration, through the formal discovery of testosterone in the 20th century, to the eventual synthesis of testosterone and identification of Leydig cells. Testosterone’s crucial role in male development and its influence on the development and maturation process of the prostate gland are also presented. The introduction of 5ARIs in the 1990s, such as finasteride, marked a significant advancement in managing BPH by reducing dihydrotestosterone (DHT) levels. The controversy regarding the therapeutic use of 5ARIs is discussed, given concerns about their association with high-grade prostate cancer and other systemic risks. Likewise, emerging evidence challenges the traditional view that testosterone exacerbates prostate conditions, suggesting that testosterone replacement therapy (TRT) may improve symptoms of low testosterone without increasing BPH symptoms, prostate cancer (PCa), or cardiovascular risk. Several new studies are discussed suggesting that low or declining testosterone level could be a risk factor for prostate tumorigenesis. This review emphasizes the need for continued research on Testosterone and 5ARI to further define their role in men’s health.

RESEARCH METHODS AND GEOINFORMATION MODELS OF CHANGES IN LAND RESOURCES OF ALMATY REGION UNDER THE INFLUENCE OF HOUSEHOLD WASTE

This article deals with the solution of scientific problems, including the development of holistic conceptual models for presenting, processing and analyzing geographic information, and comprehensively assesses the extent of the impact of regional systems on many dangerous natural and artificial processes. This makes it possible to resolve the contradiction between the need to analyze the state of various territorial systems in order to prevent the occurrence of emergencies due to the influence of natural and man-made processes.On the one hand, providing information and support in decision-making, and on the other, ensuring the provision of cartographic models of transport systems risk assessment of dangerous natural and man-made processes and their mapping. Integrated environmental assessment and modeling of industrial systems. A method for mapping payment systems and assessing the health of the population. Since the city of Almaty is a large metropolis, the ecological situation is very poor. This directly affects the ecology of the City, Public Health. We manage, process data by processing GIS data. In solving upcoming environmental problems, in developing new solutions, a special data card will come to the rescue. This will lead to solving problems from this point of view. It is possible to create monitoring maps by combining space surveys and statistical data. One of the most effective aspects of GIS data is that it allows you to optimally consider problems and work in any area. From this point of view, the GIS industry is developing rapidly. In the country, this industry is developing rapidly and is gaining a lot of demand.