Search Results (20)

Bronchopulmonary dysplasia (BPD) remains a significant complication of premature birth and neonatal intensive care. While much is known about the drivers of lung injury, few studies have addressed the interrelationships between oxidative stress, inflammation, and downstream events, such as endoplasmic reticulum (ER) stress. In this review, we explore the concept of a “destructive cycle” in which these drivers self-amplify to push the lung into a state of maladaptive repair. Animal models, primarily the hyperoxic rat pup model, support a sequential progression from the generation of reactive oxygen species (ROS) and inflammation to endoplasmic reticulum (ER) stress and mitochondrial injury. We highlight how these intersecting pathways offer not just therapeutic targets but also opportunities for interventions that reprogram system-wide responses. Accordingly, we explore the potential of systems pharmacology therapeutics (SPTs) to address the multifactorial nature of BPD. As a prototype SPT, we describe the development of N-acetyl-L-lysyl-L-tyrosyl-L-cysteine amide (KYC), a systems chemico-pharmacology drug (SCPD), which is selectively activated in inflamed tissues and modulates key nodal targets such as high-mobility group box-1 (HMGB1) and Kelch-like ECH-associated protein-1 (Keap1). Collectively, the data suggest that future therapies may require a coordinated, network-level approach to break the destructive cycle and enable proper regeneration rather than partial repair. Full article

In modern digital transactions involving government agencies, financial institutions, and commercial enterprises, reliable identity verification is essential to ensure security and trust. Traditional methods, such as submitting photocopies of ID cards, are increasingly susceptible to identity theft and fraud. To address these challenges, this study proposes a novel and robust identity verification framework that integrates super-resolution preprocessing, a convolutional neural network (CNN), and Monte Carlo dropout-based Bayesian uncertainty estimation for enhanced facial recognition in electronic know your customer (e-KYC) processes. The key contribution of this research lies in its ability to handle low-resolution and degraded facial images simulating real-world conditions where image quality is inconsistent while providing confidence-aware predictions to support transparent and risk-aware decision making. The proposed model is trained on facial images resized to 24 × 24 pixels, with a super-resolution module enhancing feature clarity prior to classification. By incorporating Monte Carlo dropout, the system estimates predictive uncertainty, addressing critical limitations of conventional black-box deep learning models. Experimental evaluations confirmed the effectiveness of the framework, achieving a classification accuracy of 99.7%, precision of 99.2%, recall of 99.3%, and an AUC score of 99.5% under standard testing conditions. The model also demonstrated strong robustness against noise and image blur, maintaining reliable performance even under challenging input conditions. In addition, the proposed system is designed to comply with international digital identity standards, including the Identity Assurance Level (IAL) and Authenticator Assurance Level (AAL), ensuring practical applicability in regulated environments. Overall, this research contributes a scalable, secure, and interpretable solution that advances the application of deep learning and uncertainty modeling in real-world e-KYC systems. Full article

In the modern era, CO₂ emissions is a popular and significant study topic. Environmental sustainability is adversely affected by CO₂ emissions, which have become the main cause of climate change. Using panel data analysis, this study investigated the connections between CO₂ emissions and economic development, capital accumulation, and the use of renewable energy. Long-term connections between variables were examined using the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators, taking into account heterogeneity and cross-sectional dependence. Additionally, the Dumitrescu–Hurlin Panel Granger Causality Test was used to assess dynamic interactions between variables. Although CH₄ emissions increase CO₂ emissions, the effects of economic growth and capital accumulation are not statistically significant, as determined using the AMG and CCEMG. Although the use of renewable energy was shown to have the potential to lower CO₂ emissions, this impact was not statistically significant. The results of the dynamic panel demonstrate that CO₂ emissions increase with capital accumulation. Although methane (CH₄) emissions significantly impact CO₂ emissions, economic growth, capital accumulation, and renewable energy use do not show statistically significant effects, highlighting the varying influences of these factors across nations. The findings of this study emphasize the need to integrate environmental regulations into capital investment strategies and adopt country-specific policies to effectively reduce CO₂ emissions. They also underscore the need to customize green legislation to the specific conditions of each nation while simultaneously advocating for further expenditures in clean energy and the formulation of policies to supplant fossil fuels. Full article

Bronchopulmonary dysplasia (BPD) is the most common complication of prematurity. Oxidative stress (OS) and inflammation are the major contributors to BPD. Despite aggressive treatments, BPD prevalence remains unchanged, which underscores the urgent need to explore more potential therapies. The endoplasmic reticulum (ER) plays crucial roles in surfactant and protein synthesis, assisting mitochondrial function, and maintaining metabolic homeostasis. Under OS, disturbed metabolism and protein folding transform the ER structure to refold proteins and help degrade non-essential proteins to resume cell homeostasis. When OS becomes excessive, the endogenous chaperone will leave the three ER stress sensors to allow subsequent changes, including cell death and senescence, impairing the growth potential of organs. The contributing role of ER stress in BPD is confirmed by reproducing the BPD phenotype in rat pups by ER stress inducers. Although chemical chaperones attenuate BPD, ER stress is still associated with cellular senescence. N-acetyl-lysyltyrosylcysteine amide (KYC) is a myeloperoxidase inhibitor that attenuates ER stress and senescence as a systems pharmacology agent. In this review, we describe the role of ER stress in BPD and discuss the therapeutic potentials of chemical chaperones and KYC, highlighting their promising role in future therapeutic interventions. Full article

Bronchopulmonary dysplasia (BPD) is the most common lung complication of prematurity. Despite extensive research, our understanding of its pathophysiology remains limited, as reflected by the stable prevalence of BPD. Prematurity is the primary risk factor for BPD, with oxidative stress (OS) and inflammation playing significant roles and being closely linked to premature birth. Understanding the interplay and temporal relationship between OS and inflammation is crucial for developing new treatments for BPD. Animal studies suggest that OS and inflammation can exacerbate each other. Clinical trials focusing solely on antioxidants or anti-inflammatory therapies have been unsuccessful. In contrast, vitamin A and caffeine, with antioxidant and anti-inflammatory properties, have shown some efficacy, reducing BPD by about 10%. However, more than one-third of very preterm infants still suffer from BPD. New therapeutic agents are needed. A novel tripeptide, N-acetyl-lysyltyrosylcysteine amide (KYC), is a reversible myeloperoxidase inhibitor and a systems pharmacology agent. It reduces BPD severity by inhibiting MPO, enhancing antioxidative proteins, and alleviating endoplasmic reticulum stress and cellular senescence in a hyperoxia rat model. KYC represents a promising new approach to BPD treatment. Full article

Bronchopulmonary dysplasia (BPD) is a lung complication of premature births. The leading causes of BPD are oxidative stress (OS) from oxygen treatment, infection or inflammation, and mechanical ventilation. OS activates alveolar myeloid cells with subsequent myeloperoxidase (MPO)-mediated OS. Premature human neonates lack sufficient antioxidative capacity and are susceptible to OS. Unopposed OS elicits inflammation, endoplasmic reticulum (ER) stress, and cellular senescence, culminating in a BPD phenotype. Poor nutrition, patent ductus arteriosus, and infection further aggravate OS. BPD survivors frequently suffer from reactive airway disease, neurodevelopmental deficits, and inadequate exercise performance and are prone to developing early-onset chronic obstructive pulmonary disease. Rats and mice are commonly used to study BPD, as they are born at the saccular stage, comparable to human neonates at 22–36 weeks of gestation. The alveolar stage in rats and mice starts at the postnatal age of 5 days. Because of their well-established antioxidative capacities, a higher oxygen concentration (hyperoxia, HOX) is required to elicit OS lung damage in rats and mice. Neutrophil infiltration and ER stress occur shortly after HOX, while cellular senescence is seen later. Studies have shown that MPO plays a critical role in the process. A novel tripeptide, N-acetyl-lysyltyrosylcysteine amide (KYC), a reversible MPO inhibitor, attenuates BPD effectively. In contrast, the irreversible MPO inhibitor—AZD4831—failed to provide similar efficacy. Interestingly, KYC cannot offer its effectiveness without the existence of MPO. We review the mechanisms by which this anti-MPO agent attenuates BPD. Full article

Dasania marina (isolate SD1D, with 98.5% sequence similarity to Dasania marina DMS 21967 KOPRI 20902) is a marine bacterium that was isolated from ballast tank fluids as part of a biofilm study in 2014. Our previous work indicated that although this strain produced no detectable biofilm, it was the only isolate to produce N-acyl homoserine lactones (AHLs) in assays using the broad-range reporter strain, Agrobacterium tumefaciens KYC55. The goal of the current study was to determine the types of AHL molecules produced by the D. marina isolate using gas chromatography–mass spectroscopy (GCMS) and C4- to C14-AHL as standards. A time course assay indicated that the D. marina strain produced the highest level of AHLs at 20 h of growth. When extracts were subjected to GCMS, detectable levels of C8- and C10-AHL and higher levels of C12-AHL were observed. Interestingly, several biofilm-forming isolates obtained from the same source also produced detectable amounts of several AHLs. Of the isolates tested, a strain designated SD5, with 99.83% sequence similarity to Alteromonas tagae BCRC 17571, produced unstable biofilms, yet detectable levels of C6-, C8-, C10- and C12-AHL, and isolate SD8, an Alteromonas oceani S35 strain (98.85% sequence similarity), produced robust and stable biofilms accompanied by detectable levels of C8- and C12-AHL. All isolates tested produced C12-AHL at higher levels than the other AHLs. Results from this study suggest that quorum sensing and biofilm formation are uncoupled in D. marina. Whether the suite of AHLs produced by this isolate could modulate biofilm formation in other strains requires further study. Full article

The charity sector impacts society significantly in many areas, including providing education, healthcare, hunger relief, drinking water, disaster relief, environmental preservation, and assistance to underserved people. The existing charity organizations have numerous limitations, such as poor management, high operation costs, and a lack of transparency in the donation execution flow. The authentication of users and institutions is a big problem in the existing system. This research resolves the issues of transparency and reliability with an immutable and traceable distributed ledger. We empower the existing centralized charity works with the electronic know-your-customer (eKYC) authentication approach and cryptographic HASH. Information privacy is implemented using the filters within smart contracts. The implementation of eKYC to ensure authenticity and to secure data flow through the channel are two significant contributions of this work. A coin-toss function for data selection and a random time delay between pieces of data are used to avoid attacks based on guesswork. We aim for this framework to send 100% of donations to the beneficiaries and become a hyper-liquid medium to fill the United Nations Sustainable Development Goals (SDG) funding gap. We also introduce the concept of service charity to broaden the ability for people to offer their services and skills as charity. Full article

Anonymity forms the basis of decentralized ecosystems, leading to an increase in criminal activities such as money laundering and illegal currency trading. Especially in blockchain-based metaverse services, activities such as preventing sexual crimes and verifying the identity of adults are becoming essential. Therefore, avatar authentication and the KYC (Know Your Customer) process have become crucial elements. This paper proposes a mechanism to achieve the KYC process by verifying user identity using smart contracts. Users obtain an SBT (Soul Bound Token) from the metaverse service provider through the DID (Decentralized Identity) credential issued during the KYC process. The identity verification of avatars occurs within smart contracts, ensuring user privacy and protection through ZKP (Zero Knowledge Proof). Tools for generating ZKP are also provided, enabling users, even those who are unfamiliar with ZKP, to use them conveniently. Additionally, an integrated wallet is offered to seamlessly manage DID credentials and SBTs. Furthermore, in case of avatar identity issues, users can request an audit by the issuer through the associated DID tokens. Full article

Funding shortages are a persistent issue, particularly for small and medium-sized enterprises (SMEs), and the problem tends to worsen cyclically. The market for factoring and invoice discounting aims to address delays in payment for commercial invoices. These involves sellers present unpaid invoices to financial organizations, typically banks, who provide an advance payment. The implementations of the factoring services without intermediaries in blockchain of the state of the art are all based on the publication on-chain of all the invoices, use know your customer (KYC) mechanisms, and over-collateralize the invoices. This article proposes a new, decentralized approach to lending services that completely eliminates intermediaries and does not require strong KYC, yet it is reasonably resilient. The approach uses liquidity pools and associated heuristics to create a model of risk compensation. In this model, a formula measures the contributed collateral to an invoice and the risk of a late invoice or non-payment, using the Kelly criterion to calculate the optimal premium for funding said invoice in the liquidity pool. The algorithm’s performance is tested in many scenarios involving several invoice amounts, collaterals, payment delays, and non-payment rates. The study also examines premium distribution policies and hack scenarios involving bogus, non-payable invoices. The outcome is a decentralized market that uses the Kelly criterion and is reasonably resilient to a wide range of invoicing scenarios, including 5% non-payment rates and 10% bogus invoices, yet provides a sound profit to liquidity providers. The algorithm’s resilience is enhanced by several premium distribution policies over partially collateralized invoices from 50 to 70%, resulting in optimal premium withdrawal policies every 30 days, making it the first protocol for loanable funds that does not require over-collateralization to be profitable and resilient. Full article

Cryptocurrencies have the potential to enable socioeconomic growth throughout the world by offering easier access to capital and financial services. However, many virtual asset service providers (VASPs) that offer cryptocurrency services lack identity management and can be accessed anonymously, which has led to their services being exploited by criminal activities such as money laundering and illegal foreign exchange. Such crimes have a negative impact on socioeconomic sustainability. Building identity systems on blockchains can help VASPs improve their identity management to combat cryptocurrency-based crimes so VASPs can better serve the social economy and achieve their sustainability goals. However, existing solutions have privacy problems because the identity provider can associate users’ identities with their wallet accounts. In addition, there is currently no solution that can support all public blockchains unconditionally, as current solutions can only support EVM-compliant blockchains or require additional work to support new blockchains. This article proposes a KYC (know your customer)-compliant identity scheme based on Ethereum using Merkle trees and smart contracts. The identity and wallet accounts are linked by the user rather than the KYC provider so, in general, no one but the user knows the association between the wallet accounts and the identity, which protects privacy. For suspicious accounts, supervisors can trace their identities and thus achieve supervision. In addition, the scheme supports identifying accounts on all public blockchains by using Merkle trees and smart contracts to bind accounts on multiple blockchains to one identity and no extra work is required. Moreover, the scheme supports users to prove that their attributes meet the requirements of VASPs by adopting the BBS+ signature and the Sigma protocol. Full article

ICOs are very attractive for investors and issuers. ICOs allow funding raising in exchange for cryptographically secure tokens, which are a means of paying for future projects or services. However, there is insignificant regulation of this process all over the world. Some countries have banned crypto assets; others have allowed the free use of tokens but do not give them official status. In this paper, the authors present an overview of the legal regulation of ICOs in different countries, dividing them into three groups: in the first group are the countries with developed legal norms and rules for conducting ICO, they have the subsequent circulation of tokens on their territory; in the second group are the countries that are most friendly to ICOs; the third group of countries has a wait-and-see attitude. The author connect the insufficient law regulation and risks of ICOs in different countries. The types of ICO risks are divided into three main categories: financial, technical, and analytical. The main ways to reduce these risks, depending on their types, are highlighted in this study. They are connected with the improvement of the legal regulation of the publication of a White Paper, the KYC procedure, and the involvement of escrow agents. Full article

Supply Chain Finance (SCF) faces the complex problem of implementing inventory, purchase order and accounts receivable financing automation in terms of transaction data trust and validation. This paper aims to explore how blockchain technology adoption solves the SCF problem using a multi-case method based on the Technological Acceptance Model (TAM). With purposive sampling, 30 cases were selected on the criteria of perceived usefulness and perceived ease of use in solving SCF problems. The results show that trust, validity and distributed ledger transaction data as perceived usefulness are the main drivers of blockchain adoption because it provides solutions to SCF automation problems such as Know Your Customer (KYC), accounting, and transaction settlement. Smart contracts offer easy and fast transactions such as in L/C export processing as perceived ease to use. Of the 30 blockchain projects, 21 offer the usefulness of automated accounts receivable financing, 15 offer easy-to-use purchase order financing and 8 offer easy-to-use inventory financing processes. This study provides the current state of blockchain technology adoption by exploring 30 real application cases in SCF globally. Blockchain advantages provide automation solutions in global supply SCF practices with smart contracts, transparency and security of distributed ledger data feature. Full article

This study aimed to perform linguistic and cross-cultural adaptation to establish a Polish version of the Lower Limb Functional Index (LLFI) as well as an evaluation of the psychometric properties. This was a two-stage, cross-sectional study. The first stage—linguistic and cultural adaptation, complied with the International Society for Pharmacoeconomics and Outcomes Research guidelines to produce the Lower Limb Functional Index, Polish version (LLFI-PL). The subjects were recruited to the second stage of the study from a sample of convenience (n = 125, age $\stackrel{-}{x}$ = 52.86 ± 19.53 years, 56% female, symptoms duration $\stackrel{-}{x}$ = 17.69 ± 18.39 weeks). Baseline reliability was performed on the LLFI-PL with retest period at 3–7 days. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC), EuroQol Health Questionnaire 5-Dimensions 5-Level (EQ-5D-5L), and an 11-point Pain Numerical Rating Scale (P-NRS) were completed to assess the validity of the LLFI-PL. Statistical analysis showed high internal consistency (α = 0.94), and excellent test–retest reliability (ICC_2.1 = 0.96). The measurement error was SEM = 1.69% with MDC₉₀ = 3.93%. Construct validity demonstrated strong correlations between the LLFI-PL and WOMAC (r = 0.81) and moderate correlations with the EQ-5D-5L (r = −0.63) and P-NRS (r = −0.39). Exploratory factor analysis confirmed a single-factor structure. The LLFI-PL is a psychometrically sound questionnaire for Polish-speaking patients with lower limb musculoskeletal conditions. The results support findings from the previous original English, Spanish, and Turkish versions. Full article

Plaque psoriasis is a common inflammatory condition of the skin characterized by red, flaking lesions. Current therapies for plaque psoriasis target many facets of the autoimmune response, but there is an incomplete understanding of how oxidative damage produced by enzymes such as myeloperoxidase contributes to skin pathology. In this study, we used the Aldara (Imiquimod) cream model of plaque psoriasis in mice to assess myeloperoxidase inhibition for treating psoriatic skin lesions. To assess skin inflammation severity, an innovative mouse psoriasis scoring system was developed. We found that myeloperoxidase inhibition ameliorated psoriasis severity when administered either systemically or topically. The findings of this study support the role of oxidative damage in plaque psoriasis pathology and present potential new therapeutic avenues for further exploration. Full article