Global Threat Research Articles

ATTITUDES AND AWARENESS OF THE POPULATION OF CENTRAL AND WESTERN REGIONS OF UKRAINE TOWARDS VACCINATION

In the modern world, vaccination is the most eff ective and evidence- based method of preventing the onset and severity of infectious diseases. Today, the WHO has identifi ed vaccine hesitancy as a global public health threat [25]. The social and cultural background of people infl uences their perception of vaccines, which prompted us to investigate this problem. Aim. To study the infl uence of sociodemographic factors on vaccination attitudes of children and adults in the central and western regions of Ukraine.Materials and methods. A cross- sectional study was conducted, which included a survey of the population of diff erent social status. The study was conducted in accordance with the tenets of the Declaration of Helsinki. The study protocol was approved by the bioethics committee. We also analyzed literature data from PubMed, Medscape and CSC. The work was performed within the framework of the research project 0122U000039 «Improvement of methods of diagnosis, treatment and rehabilitation of the most common diseases of childhood». No confl icts of interest exist.Research results and discussion. 1000 respondents were interviewed by questionnaire from Kyiv, Cherkasy, Kirovograd, Khmelnytsky, Zhytomyr, Chernivtsi, Ternopil, Rivne, Volyn, Ivano- Frankivsk, Lviv regions. The data obtained indicate that barriers to vaccination are caused by low awareness of vaccination, excessive negative infl uence of opinion leaders, prevalence of myths and falsifi cations about vaccination, lack of health care resources and low supply of recommended vaccines, and forced migration. Low awareness and low vaccination coverage are also associated with low awareness among health workers who do not work directly with vaccines, falsifi cation of vaccination data, and the presence of anti-vaccine health workers. The negative attitude of parents towards vaccination is also very important, as it aff ects their children.Conclusions.1. Fear of side eff ects, long-term complications, and doubts about the quality of vaccines have been identifi ed as factors in vaccine refusal.2. The most common groups of vaccine refusers are the elderly (53.3 %) and men (16.8 %).3. The high cost of vaccines that are not included in the list of mandatory vaccines is one of the reasons for the decrease in vaccination rates.4. Improved communication between the doctor and the patient is one of the factors increasing the vaccination rate among the population.5. Information about the availability of vaccines and places of vaccination, peculiarities of the post-vaccination period and information about the possible consequences of ignoring vaccination should be provided in the media (television, radio), especially among the elderly.

Activated Charcoal-Alginate Platform for Simultaneous Local Delivery of Bioactive Agents: At the Nexus of Antimicrobial and Cytotoxic Activity of Zn2+ Ions

Antimicrobial resistance (AMR) is a global public health threat that affects cancer patients more than the general population. In this work, a composite system based on Zn-alginate hydrogel and activated charcoal (AC) particles that, upon contact with physiological fluids, simultaneously releases bioactive agents (Zn2+ and AC particles impregnated with povidone–iodine) was designed to locally address specific problems characteristic for malignant wounds (MWs). This composite was comprehensively investigated in vitro regarding its morphology (field-emission scanning electron microscopy), Zn2+ release (flame atomic absorption spectrometry), iodine adsorption and desorption from AC particles (energy dispersive X-ray analysis and UV–visible spectroscopy) as well as its antimicrobial and antitumor activity. With respect to the ongoing AMR crises, antimicrobial activity was tested against a wide range of wild multi-drug resistant bacterial and yeast strains, all isolated from patient wounds. Since Zn2+ ions proved to be selectors of resistant strains of bacteria, the synergistic activity of AC particles and adsorbed iodine was shown to be crucial for excellent antibacterial activity. On the other hand, the synergy of AC particles and Zn2+ ions showed an equally strong antifungal effect. In addition, antimicrobial concentrations of Zn2+ ions showed cytotoxic activity against two cancer cell lines derived from cancers affecting skin either as metastatic cancer (breast cancer MDA-MB-453 cell line) or primary cancer of the skin (malignant melanoma Fem-X cell line), which enables Zn2+ ions to be further investigated as potent local agents targeting malignant cells.

Advances in Discovery and Design of Anti-influenza Virus Peptides.

The influenza virus, a well-known pathogen that causes respiratory illness, remains an important global health threat because of the significant morbidity and mortality rates of people infected with the virus annually. The influenza virus undergoes frequent antigenic variation, and with the increasing frequency of resistant influenza strains against existing antiviral drugs, there is an urgent need for the development of new anti- influenza treatment strategies. Peptides have the potential to offer high potency, selectivity, and relatively low drug resistance. As such, the design and screening of novel anti- influenza virus peptides with high potency have become increasingly important in an effort to fight global influenza epidemics. Herein, we introduce three approaches to developing anti-influenza virus peptides: discovery from natural products, library construction for antiviral peptide screening, and rational design based on functional regions of influenza viral proteins. This review summarizes recent progress in the discovery and design of anti-influenza virus peptides over the past 20 years.

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.

The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment. This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries. A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology. Advanced ML algorithms were harnessed to sculpt predictive models that ascertain resistance to quintessential antibiotics, particularly levofloxacin and ciprofloxacin, by using the amassed spectral data. Our ML models revealed remarkable proficiency in forecasting antibiotic resistance, with the random forest classifier emerging as particularly effective in predicting resistance to both levofloxacin and ciprofloxacin, achieving the highest area under the curve of 0.95. Performance metrics across different models, including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score, were detailed, underlining the potential of these algorithms in aiding the development of precision treatment strategies. This investigation highlights the synergy between MALDI-TOF MS and ML as a beacon of hope against the escalating threat of antibiotic resistance. The advent of AI-CDSS heralds a new era in clinical diagnostics, promising a future in which rapid and accurate resistance prediction becomes a cornerstone in combating infectious diseases. Through this innovative approach, we answered the challenge posed by KP and other multidrug-resistant pathogens, marking a significant milestone in our journey toward global health security.

Risk Analysis of Strategic Commodities in Customs Procedures in Relation to Global Security Threats

Risk Analysis of Strategic Commodities in Customs Procedures in Relation to Global Security Threats

Epidemiological and molecular characteristics of carbapenem-resistant Klebsiella pneumoniae from pediatric patients in Henan, China

PurposeCarbapenem-resistant Klebsiella pneumoniae (CRKP) is an emerging global threat, whereas its epidemiological characteristics in children are rarely reported. This study aims to analyze clinical and epidemiological characteristics of CRKP from children in Henan, China.MethodsCRKP strains were isolated from pediatric patients, and the antimicrobial susceptibility of CRKP was determined using broth microdilution methods. The epidemiological characteristics of CRKP, including specimen sources, clinical data, carbapenemase types, virulence factors, MLST and PBRT typing were analyzed.ResultsIn total, 108 CRKP isolates were isolated from specimens including sputum, blood and urine, mainly from preterm pediatric department and internal medical intensive care unit (ICU). Newborns and staying in the ICU were risk factors for crude mortality. 107 isolates exhibited a multi-drug resistant (MDR) phenotype, and one isolate was extensively drug-resistant (XDR). Bacterial susceptibility to colistin, tigecycline and trimethoprim/sulfamethoxazole was 98.10%, 78.50% and 91.43%, respectively. Carbapenemase blaKPC (86.11%) was predominant, followed by blaNDM (5.56%) and blaIMP (2.78%). Two strains co-harbored blaKPC-blaNDM, one had blaKPC-blaIMP, whereas three isolates did not carry any of the analyzed carbapenemase genes. All strains possessed fimH, and 98% of the isolates possessed mrkD. Hypervirulent factors rmpA2 and iucA showed high positive rates (71.30% and 49.07%), with 48.15% of strains containing both genes. MLST analysis identified nine distinct sequence types (STs), with ST11 (82.41%) being the most common, followed by ST2154 (4.63%) and ST307 (3.70%). PBRT analysis revealed IncFII (85.19%) as the most prevalent plasmid.ConclusionIn summary, this study reported the epidemiological features of CRKP in pediatric patients in Henan, China, highlighting the high prevalence of multi-drug-resistant and hypervirulent strains, and underscoring the significance of continuous surveillance.

Lignin-Derived Gold-Titanium Dioxide Nanophotocomposites as Potent Photoactivatable Probes for Microbial Inactivation.

The overuse of antibiotics has accelerated antibiotic resistance, and it is a significant global threat to public health. To combat the rising threat of drug-resistant microbes, antimicrobial photodynamic therapy (APDT) has emerged as a promising alternative therapeutic strategy. This study focuses on the synthesis of eco-friendly lignin-derived gold-titanium dioxide nanophotocomposites (L@Au-TiO2 NCs). Lignin was utilized as a sustainable precursor for the synthesis of L@Au-TiO2 NCs. The gold and TiO2 nanoparticles possess inherent photodynamic properties, and thus the developed L@Au-TiO2 NCs exhibit enhanced antimicrobial efficacy due to the synergistic combination of their attributes. The antimicrobial potential of the L@Au-TiO2 NCs was evaluated against various microbial strains (Escherichia coli, Bacillus megaterium, and Candida tropicalis) under dark and green light conditions. The outcome of this study highlights the promising potential of L@Au-TiO2 NCs for photodynamic antimicrobial applications. The L@Au-TiO2 nanophotocomposites could be explored in the fields of medicine and nanotechnology to introduce innovative ideas into the biomedical field.

FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation.

With the swift advancement of technology and growing popularity of internet in business and communication, cybersecurity posed a global threat. This research focuses new Deep Learning (DL) model referred as FinSafeNet to secure loose cash transactions over the digital banking channels. FinSafeNet is based on a Bi-Directional Long Short-Term Memory (Bi-LSTM), a Convolutional Neural Network (CNN) and an additional dual attention mechanism to study the transaction data and influence the observation of various security threats. One such aspect is, relying these databases in most of the cases imposes a great technical challenge towards effective real time transaction security. FinSafeNet draws attention to the attack and reproductive phases of Hierarchical Particle Swarm Optimization (HPSO) feature selection technique simulating it in a battle for extreme time performance called the Improved Snow-Lion optimization Algorithm (I-SLOA). Upon that, the model then applies the Multi-Kernel Principal Component Analysis (MKPCA) accompanied by Nyström Approximation for handling the MKPCA features. MKPCA seeks to analyze and understand a non-linear structure of data whereas, Nyström Approximation reduces the burden on computational power hence allows the model to work in situations where large sizes of datasets are available but with no loss of efficiency of the model. This causes FinSafeNet to work easily and still be able to make accurate forecasts. Besides tackling feature selection and dimensionality reduction, the model presents advanced correlation measures as well as Joint Mutual Information Maximization to enhance variable correlation analysis. These improvements further help the model to detect the relevant features in transaction data that may present a threat to the security of the system. When tested on commonly used database for testing banks performance, for instance the Paysim database, FinSafeNet significantly improves upon the previous and fundamental approaches, achieving accuracy of 97.8%.

Multimodal Sensemaking and Sensegiving Processes of Discursive Threat Appraisal in Environmental Crisis Communication

ABSTRACTThis study investigates how multimodal sensemaking and sensegiving processes of discursive threat appraisal are employed by global movements in their environmental crisis communication when disclosing how corporate commitments are failing to reduce the global plastic pollution. The theoretical framework includes perspectives on global sticky crises, threat appraisal, framing, crisis sensemaking and sensegiving, and multimodal discourse. Empirically, a series of brand audits reports of #breakfreefromplastic global movement are systematically examined. The analytical focus transcends the usual monomodal approach and is directed towards the multimodal interplay that builds strategic discourses through images and texts. Findings details, on the one hand, the multimodal discursive sensemaking processes of content enrichment and appeal bolstering as well as their outcomes related to the building of common sense, new sense, and non‐sense; on the other hand, they clarify how prognostic, diagnostic, and motivational framing tasks are accomplished in environmental crisis sensegiving by the global movement. This study provides insights useful to corporations when reevaluating their own crisis sensemaking and sensegiving in corporate communications and, ultimately, contribute to changing risky corporate behaviour toward more effective and ethical environmental crisis prevention and communication.

Antimicrobial Prescribing Patterns in GP Practices in Northern Ireland

Introduction: Antimicrobial resistance (AMR) is a global health threat requiring immediate attention as it is set to cause ten million deaths worldwide by 2050, overtaking that of cancer. Continuation of overuse and/or misuse of these crucial medicines will prevent future generations from reaping the benefits, as the pandemic of AMR spirals out of control. Aims: The primary aim of this study was to investigate antimicrobial prescribing patterns in General Practices throughout Northern Ireland. A secondary aim was to analyse the impact of the COVID-19 pandemic on antimicrobial prescribing and consumption patterns in GP practices in Northern Ireland. Methods: A retrospective, cross-sectional quantitative study was designed to measure, analyse, and evaluate the antimicrobial prescribing patterns within GP practices in Northern Ireland, using open access Business Services Organisation (BSO) data. Results: A total of 3,168.78 kg of antibacterial drugs were prescribed in primary care throughout the duration of the study. Penicillins were the most prescribed class (59.79%), followed by tetracyclines (10.68%) and macrolides (9.53%). Access group antibiotics were the most frequently prescribed (79.35%), followed by Watch group antibiotics (20.64%), with Reserve group antibiotics equating to nearly 0% despite being prescribed. The Derry GP Federation prescribed and dispensed the greatest amount of antibiotics overall in Northern Ireland (10.90%). Despite there being no significant difference in antibiotic prescribing amongst GP federations prior to and during the COVID-19 pandemic (unpaired t-test, p > 0.05), there were differences in prescribing of individual drug classes throughout this period. Conclusions: Despite meeting World Health Organisation (WHO) targets, GP practices within Northern Ireland must achieve more to further reduce antimicrobial consumption. Although antibiotic prescribing rates here are on the decline, there was no significant difference in prescribing amongst GP federations pre- and midst-COVID-19 pandemic, thus sufficient strategies such as increased communication between colleagues and supportive measures must be implemented within GP practices to enhance antimicrobial stewardship (AMS) across Northern Ireland.

Antibiotic Prescribing Practices in a Tertiary Care Teaching Hospital: A Retrospective Cross-Sectional Analysis.

Background Antibiotics are among the most frequently prescribed medications in hospitals, yet a significant portion of their use is inappropriate, contributing to the growing global threat of antimicrobial resistance (AMR). In Pakistan, AMR has reached alarming levels with the rise of multi- and extensively drug-resistant bacteria. This study evaluates antibiotic prescribing practices and the use of culture sensitivity (CS) testing to assess the appropriateness of antibiotic therapy. Methods This cross-sectional retrospective study was conducted in a 500-bed tertiary care teaching hospital in Islamabad, Pakistan, analyzing inpatient records from 2020 to 2022. From over 5000 patient files, 1012 met the inclusion criteria and were reviewed. The study assessed the rationality of antibiotic prescriptions based on the evidence of infection (EoI), clinical parameters, and the presence or absence of CS testing. Statistical analyses, including Chi-square tests, logistic regression, and Cox proportional hazards regression, were applied to determine the association between antibiotic use and patient outcomes. Results Among the 1,012 patients analyzed, 91.8% (n = 929) received one or more antibiotics. However, 30% (n = 274) of these prescriptions were issued without any documented EoI.Only 17.5% of patients underwent CS testing. Patients exposed to five or more antibiotics had a 2.5-fold increased risk of ICU mortality (HR = 2.50, p < 0.001). A positive correlation (r = 0.42, p < 0.001) was found between the number of antibiotics prescribed and the length of hospitalization. Conclusion The findings of this study reveal a high rate of inappropriate antibiotics prescribed without EoI and CS testing. The results emphasize the urgent need for comprehensive Antibiotic Stewardship Programs (ASPs) in hospital settings, particularly focusing on mandatory CStesting protocols. By reducing irrational antibiotic use, these initiatives can significantly mitigate the rise of AMRglobally, especially in resource-limited settings. Implementing ASPs not only optimizes antibiotic use but also aligns with the WHO recommendations, demonstrating the effectiveness of multifaceted interventions in minimizing resistance and improving patient outcomes.

Detection and molecular characterization of lumpy skin disease and bovine papular stomatitis viruses in lumpy skin disease-suspected outbreaks in Tanzania.

Lumpy Skin Disease (LSD) is endemic in sub-Saharan countries and is currently a global threat to the cattle industry. Information on the circulating Capripoxvirus lumpyskinpox, formerly known as Lumpy Skin Disease Virus (LSDV), and other poxviruses infecting cattle is very scant in Tanzania. The current study aimed to confirm and characterize LSDV and other poxviruses infecting cattle, from LSD suspected outbreaks in Tanzania. A total of 24 samples were collected from four LSD suspected outbreaks reported in Tanzania between February and May 2023. Samples were screened for LSDV genome by real-time PCR and then subjected to a high-resolution multiplex melting (HRM) assay where 10 samples were positive for Capripoxvirus (CaPV) and one sample was Parapoxvirus (PPV) positive. Four LSDV genes; RPO30, GPCR, EEV glycoprotein and B22R and the partial B2L gene of PPVs were analyzed. All targeted LSDV genes from the Tanzanian isolates showed 100% similarity and isolates clustered with commonly circulating LSDV field isolates. Furthermore, the single nucleotide polymorphism (SNP) at position 240 (A-> G) of the EEV gene differentiates the Tanzanian LSDVs from the group of ancient Kenyan LSDV isolates while the B22R sequences of the Tanzanian LSDV isolates differed from the LSDV Neethling and LSDV KSGP-0240 derived vaccines. Sequence analysis of the partial B2L gene of the Tanzanian parapoxvirus bovinestomatitis, formerly known as Bovine papular stomatitis virus (BPSV) showed a different BPSV strain circulating compared to publicly available sequences. These findings confirm the presence of LSDV in Tanzania, which suggesting the need for establishing an effective control program and continuous monitoring. The presence of a typical profile for Tanzania BPSV is an indication that, although never reported before, BPSV is established in the country therefore this virus should be included in the differential diagnosis of LSDV.

Multiple Machine Learning Identifies Key Gene PHLDA1 Suppressing NAFLD Progression.

Non-alcoholic fatty liver disease (NAFLD) poses a serious global health threat, with its progression mechanisms not yet fully understood. While several molecular markers for NAFLD have been developed in recent years, a lack of robust evidence hampers their clinical application. Therefore, identifying novel and potent biomarkers would directly aid in the prediction, prevention, and personalized treatment of NAFLD. We downloaded NAFLD-related datasets from the Gene Expression Omnibus (GEO). Differential expression analysis and functional analysis were initially conducted. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) and multiple machine learning strategies were employed to screen and identify key genes, and the diagnostic value was assessed using Receiver Operating Characteristic (ROC) analysis. We then explored the relationship between genes and immune cells using transcriptome data and single-cell RNA sequencing (scRNA-seq) data. Finally, we validated our findings in cell and mouse NAFLD models. We obtained 23 overlapping differentially expressed genes (DEGs) across three NAFLD datasets. Enrichment analysis revealed that DEGs were associated with Apoptosis, Parathyroid hormone synthesis, secretion and action, Colorectal cancer, p53 signaling pathway, and Biosynthesis of unsaturated fatty acids. After employing machine learning strategies, we identified one gene, pleckstrin homology like domain family A member 1 (PHLDA1), downregulated in NAFLD and showing high diagnostic accuracy. CIBERSORT analysis revealed significant associations of PHLDA1 with various immune cells. Single-cell data analysis demonstrated downregulation of PHLDA1 in NAFLD, with PHLDA1 exhibiting a significant negative correlation with macrophages. Furthermore, we found PHLDA1 to be downregulated in an in vitro hepatic steatosis cell model, and overexpression of PHLDA1 significantly reduced lipid accumulation, as well as the expression of key molecules involved in hepatic lipogenesis and fatty acid uptake, such as FASN, SCD-1, and CD36. Additionally, gene set enrichment analysis (GSEA) pathway enrichment analysis suggested that PHLDA1 may influence NAFLD progression through pathways such as Cytokine Cytokine Receptor Interaction, Ecm Receptor Interaction, Parkinson's Disease, and Ribosome pathways. Our conclusions were further validated in a mouse model of NAFLD. Our study reveals that PHLDA1 inhibits the progression of NAFLD, as overexpression of PHLDA1 significantly reduces lipid accumulation in cells and markedly decreases the expression of key molecules involved in liver lipogenesis and fatty acid uptake. Therefore, PHLDA1 may emerge as a novel potential target for future prediction, diagnosis, and targeted prevention of NAFLD.

Natural Antimicrobial Agents from Algae: Current Advances and Future Directions.

Infectious diseases have significantly shaped human history, leading to significant advancements in medical science. The discovery and development of antibiotics represented a critical breakthrough, but the rise of antibiotic-resistant pathogens now presents a serious global health threat. Due to the limitations of current synthetic antimicrobials, such as toxicity and environmental concerns, it is essential to explore alternative solutions. Algae, particularly microalgae and cyanobacteria, have emerged as promising sources of bioactive antimicrobial compounds. This review provides a comprehensive analysis of the antimicrobial properties of algal-derived compounds, including polysaccharides, fatty acids, and phenols, which have shown effectiveness against multi-drug-resistant bacteria. A co-occurrence bibliometric analysis using VOSviewer highlighted five key research clusters: antibiotic resistance, algal extracts, biosynthesis, water treatment, and novel pharmacological compounds. Furthermore, the primary mechanisms of action of these bioactive compounds, such as the inhibition of protein synthesis and cell membrane disruption, were identified, demonstrating their potential against both common and multi-resistant pathogens. Future research should prioritize optimizing algal biomass production, utilizing genetic and metabolic engineering, and creating innovative delivery systems to enhance the efficient production of bioactive compounds.

Detection of Carbapenemase-Producing Enterobacterales: A Comparative Analysis of Available Phenotypic Methods

Background: Carbapenems serve as a critical last-line defence against infections from multidrug-resistant Enterobacterales. The increasing prevalence of CRE (carbapenem-resistant Enterobacterales) poses significant challenges in clinical settings. This greatly complicates the handling of gram-negative bacilli (GNB) infections and represents a significant global health threat. Aim: This study evaluates and contrasts different phenotypic techniques used to identify carbapenemase-producing Enterobacterales isolated from various clinical samples. Objectives: To compare the accuracy and reliability of Combined Disc Test (CDT) and Modified Carbapenem Inactivation Method/EDTA - Carbapenem Inactivation Method (mCIM/eCIM) in identifying Metallo-beta-lactamase (MBL)-producing Enterobacterales. Methods: All clinical specimens submitted for culture and sensitivity testing at the Department of Microbiology were analysed to isolate and identify Enterobacterales. Carbapenemase production was assessed through using the phenotypic CDT Confirmation was carried out using the mCIM and eCIM in accordance with Clinical and Laboratory Standards Institute (CLSI) guidelines. Results: During a two-year period, 254 strains of Enterobacterales were isolated. Among those, 80/254 (31.49%) isolates exhibited resistance to the Imipenem (IMP) disc. The CDT identified 30/80 (37.5%) isolates as serine carbapenemase producers and 50/80 (62.5%) isolates as MBL producers. In comparison, the mCIM/eCIM methods detected 26/80 (32.5%) isolates as serine carbapenemase producers, 48/80 (60.0%) isolates as MBL producers, and 6/80 (7.5%) isolates were tested negative for carbapenemase production. Conclusion: This study evaluates the precision and effectiveness of the mCIM/eCIM and CDT methods for identifying CRE. The combination of the mCIM and eCIM tests may be a more reliable phenotypic method for detecting carbapenemase compared to the CDT.

The 2024 Outbreak of Parvovirus B19 as a Global Obstetrical Threat Insights From an Obstetrics Referral Center in Northern Italy.

A significant increase in Parvovirus B 19 (B19V) infections has been reported in the last months in some European countries. This outbreak could be highly detrimental for pregnant women, considering the capacity of the virus to harm the fetus. However, the magnitude and spread of this outbreak is yet unclear. Evidence from other areas is required and there is the need to focus more on the impact on pregnancy. To this aim, pregnant women with B19V infection who were managed in a referral hospital located in Milan, Northern Italy were reviewed. The primary aim was comparing the number of ascertained cases of B19V infection in the period January-July 2024 to the number of cases recorded in the previous 9 years (2015-2023). Overall, the number of B19V infections markedly increased in the first 7 months of 2024. Until 2023, the number of cases per year were below 7, with no cases reported in 2020-2022, while in the period January-July 2024, the number raised to 59 (p < 0.001). Maternal characteristics and fetal outcomes before and after January 2024 did not differ. In conclusion, Italy is also involved in the ongoing outbreak of B19V infection and pregnant women are exposed to this threat. Synopsis: An outbreak of Parvovirus B19 infections is currently ongoing in Italian pregnant women.

Tenebrio molitor (Coleoptera: Tenebrionidae) as an alternative host for the study of pathogenicity in Candida auris

BackgroundCandida auris, a multidrug-resistant fungal pathogen, has emerged as a significant global health threat due to its high transmission and mortality rates, especially in healthcare settings. ObjectiveThis study aimed to establish the larvae of the coleopteran Tenebrio molitor (mealworm) as an in vivo model to evaluate the virulence of different C. auris strains. MethodsT. molitor larvae were inoculated with varying doses and strains of C. auris. Mortality rates were monitored, melanization responses, and phenoloxidase activity were assessed. Histopathological analyses were conducted to observe tissue invasion by the yeast cells. Additionally, a biofilm formation test was included as a complementary analysis to determine if biofilm production would influence the virulence of the C. auris strains. ResultsA dose-dependent increase in mortality was observed, with the highest fungal load leading to the highest mortality rates. The study also revealed significant differences in virulence among the strains, with those from Kuwait and the reference strain CBS 10913 showing the highest pathogenicity. Melanization rates were significantly higher in infected larvae, indicating an active immune response. The histopathological analysis revealed the presence of C. auris cells within the tissue of T. molitor larvae. However, the biofilm formation complementary test did not show a significant difference in virulence among the different clades of C. auris. ConclusionThe T. molitor model effectively demonstrated the pathogenic potential and virulence differences of C. auris strains. Strains from Kuwait and the reference strain CBS 10913 exhibited the highest virulence, causing 100% mortality within 24 hours. The model also highlighted significant biofilm formation and melanization responses, correlating with fungal burden. This insect model provides a valuable and cost-effective tool for preliminary virulence screening of clinical yeast strains, offering insights into host-pathogen interactions and the potential for evaluating antifungal treatments in vivo.

Fe-based nanozyme with photothermal activity prepared from polymerization-induced self-assembly assays boosts the recovery of bacteria-infected wounds

Nowadays, the overuse of antibiotics has escalated bacterial infections into an increasingly severe global health threat. Developing non-antibiotic treatments has emerged as a promising strategy for treating bacterial infections. Notably, nanozyme-based composite materials have garnered growing interest. Therefore, the efficient preparation of nanozyme is important. Herein, we have presented an efficient method to prepare Fe-based nanozyme through polymerization-induced self-assembly assay to kill bacteria efficiently, which could significantly enhance the healing of infected wounds. Through polymerization-induced self-assembly assay, a large number of uniformly sized micelles, bearing imidazole groups, could be efficiently prepared. These nanoparticles subsequently chelate with Fe ions, followed by pyrolysis and etching processes, resulting in the production of uniformly small-sized nanozymes with high adsorption activity in the near-infrared region. The composite materials could effectively eradicate bacteria via a synergistic strategy of photothermal and catalytic therapies under infected microenvironments. In vivo animal models with full-thickness wounds showed that combination therapy not only eradicates 98 % of the bacteria but also significantly accelerates wound healing. This work underscores the utility of polymerization-induced self-assembly in the preparation of nanozymes and reveals promising applications of nanozymes in wound healing. Statement of significanceThis research introduces a functional nanozyme with photothermal activity, synthesized through polymerization-induced self-assembly, offering a promising non-antibiotic strategy to combat bacterial infections. This strategy enhances wound healing by combining photothermal and catalytic therapies, effectively eradicating drug-resistant bacteria while minimizing damage to healthy tissue. Our findings hold significant implications for the development of advanced antibacterial treatments and offer a robust assay to prepare nanozyme with small sizes. The prepared functional nanoparticles have a potential in wound healing, addressing a critical need in the face of rising antibiotic resistance.

Targeting the Ubiquitin Proteasome System to Combat Influenza A Virus: Hijacking the Cleanup Crew.

Influenza A virus (IAV) remains a significant global public health threat, causing substantial illness and economic burden. Despite existing antiviral drugs, the emergence of resistant strains necessitates alternative therapeutic strategies. This review explores the complex interplay between the ubiquitin proteasome system (UPS) and IAV pathogenesis. We discuss how IAV manipulates the UPS to promote its lifecycle, while also highlighting how host cells utilise the UPS to counteract viral infection. Recent research on deubiquitinases as potential regulators of IAV infection is also addressed. By elucidating the multifaceted role of the UPS in IAV pathogenesis, this review aims to identify potential targets for novel therapeutic interventions.

Genotypic Antimicrobial Resistance Profiles of Diarrheagenic Escherichia coli and Nontyphoidal Salmonella Strains Isolated from Children with Diarrhea and Their Exposure Environments in Ethiopia.

Antimicrobial resistance (AMR) poses a significant global threat, particularly in low- and middle-income countries, such as Ethiopia, where surveillance is limited. This study aimed to predict and characterize the AMR profiles of diarrheagenic Escherichia coli (DEC) and nontyphoidal Salmonella (NTS) strains isolated from human, animal, food, and environmental samples using whole genome sequencing. A total of 57 NTS and 50 DEC isolates were sequenced on an Illumina NextSeq 550. The ResFinder and PointFinder tools were employed to identify antimicrobial resistance genes (ARGs) and point mutations. Salmonella serotypes were determined using SeqSero. The analysis identified at least one ARG in every NTS sample and 78% of the DEC isolates, with 22 distinct ARGs in the NTS samples and 40 in the DEC samples. The most prevalent ARGs were aac(6')-Iaa and aph(3')-Ib, which predict aminoglycoside resistance in 100% of NTS and 54% of DEC isolates, respectively. Other commonly identified ARGs include sul2, aph(6)-Id, blaTEM-1B , and tet(A), which confer resistance to folate inhibitors, aminoglycosides, β-lactams, and tetracycline. Some ARGs predicted phenotypic multidrug resistance in both DEC and NTS isolates. All identified β-lactam ARGs, except for blaTEM -1D, conferred resistance to more than three antibiotics. Interestingly, blaCTX- M-15 was found to confer resistance to nine antibiotics, including third-generation cephalosporins, in 18% of DEC and 3.5% of NTS isolates. DEC isolates from children exhibited the highest ARG diversity. Notably, genes such as aph(3″)-Ib, aph(6)-Id, sul2, and tet(A) were detected across all sample types, including water sources, although some ARGs were exclusive to specific sample types. Point mutations mediating AMR were detected in several genes, with mutations associated with nucleotide substitution being the most frequent. This genotypic AMR profiling revealed the presence of widespread drug-resistant NTS and DEC strains in Ethiopia. Robust and sustained AMR surveillance is essential for monitoring the emergence and spread of these resistant pathogens.