Malaria is a serious and, in some unfortunate cases, fatal disease caused by a parasite of the Plasmodium genus. It predominantly occurs in tropical areas where it is transmitted through the bite of an infected Anopheles mosquito. The pathogenesis of malaria is complex and incompletely elucidated. During blood-stage infection, in response to the presence of the parasite, the hosts immune system produces proinflammatory cytokines including IL-6, IL-8, IFN-γ, and TNF, cytokines which play a pivotal role in controlling the growth of the parasite and its elimination. Regulatory cytokines such as transforming growth factor- (TGF-) β and IL-10 maintain the balance between the proinflammatory and anti-inflammatory responses. However, in many cases, cytokines have a double role. On the one hand, they contribute to parasitic clearance, and on the other, they are responsible for pathological changes encountered in malaria. Cytokine-modulating strategies may represent a promising modern approach in disease management. In this review, we discuss the host immune response in malaria, analyzing the latest studies on the roles of pro- and anti-inflammatory cytokines.

Cystic echinococcosis (CE) is a zoonosis caused by metacestodes, the larval stage of Echinococcus granulosus. Although the World Health Organization (WHO) has defined CE as a neglected disease, it is the second most important foodborne parasitic disease, and it remains an important public health issue, considering its zonal endemicity and potential morbidity. The control and prevention of CE is a relevant WHO target, especially from a One Health perspective, as the disease affects not only animals and humans but also the food chain. Since not all countries have a CE surveillance strategy or reporting system and specific management guidelines, recent epidemiological data are relatively scarce, and research concerning the specific geographical distribution of the disease is ongoing. To add new information to the subject, we have analyzed and collected data from national guidelines and several medical databases. Out of the 751 research articles that were originally identified, only 52 were included in the investigation after applying specific inclusion and exclusion criteria. Notable international projects that have provided significant contributions and had a positive impact are presented. The available data were correlated with WHO recommendations on the subject, thus showcasing the measures taken and those that are still needed to properly control the disease’s spread.

Healthcare-associated infections (HAIs), previously known as nosocomial infections, represent a significant threat to healthcare systems worldwide, prolonging patient hospital stays and the duration of antimicrobial therapy. One of the most serious consequences of HAIs is the increase in the rate of antibiotic resistance (AR) generated by the prolonged, frequent, and sometimes incorrect use of antibiotics, which leads to the selection of resistant bacteria, making treatment difficult and expensive, with direct consequences for the safety of patients and healthcare personnel. Therefore, timely and accurate diagnosis of HAIs is mandatory to develop appropriate infection prevention and control practices (IPC) and new therapeutic strategies. This review aimed to present the prevalence, risk factors, current diagnosis, including artificial intelligence (AI) and machine learning approaches, future perspectives in combating HAIs causative bacteria (phage therapy, microbiome-based interventions, and vaccination), and HAIs surveillance strategies. Also, we discussed the latest findings regarding the relationships of AR with climate change and environmental pollution in the context of the One Health approach. Phage therapy is an emerging option that can offer an alternative to ineffective antibiotic treatments for antibiotic-resistant bacteria causing HAIs. Clinical trials dealing with vaccine development for resistant bacteria have yielded conflicting results. Two promising strategies, fecal microbiota transplantation and probiotic therapy, proved highly effective against recurrent Clostridium difficile infections and have been shown to reduce HAI incidence in hospitalized patients undergoing antibiotic therapy. Artificial intelligence and machine learning systems offer promising predictive capabilities in processing large volumes of clinical, microbiological, and patient data but require robust data integration. Our paper argues that HAIs are still a global challenge, requiring stringent IPC policies, computer vision, and AI-powered tools. Despite promising avenues like integrated One Health approaches, optimized phage therapy, microbiome-based interventions, and targeted vaccine development, several knowledge gaps in clinical efficacy, standardization, and pathogen complexity remain to be answered.

Background. Urinary tract infections (UTIs) caused by Uropathogenic Escherichia coli (UPEC) are among the most common infections worldwide, including Romania. To the best of our knowledge, this is the first study performed on a significant number of community-acquired (CA) UPEC strains isolated from Romanian outpatients, aiming to evaluate and establish potential correlations among the phylogenetic groups (PG), resistance profiles, and the virulence factors (VF) genes of the CA-UPEC isolates. Materials/Methods. The present study was performed on a total of 787 UPEC nonrepetitive isolates consecutively isolated during one month from outpatients with CA-UTIs, visiting one of the biggest laboratories in Bucharest, Romania, receiving patients from all over the country. The strains identification was performed by MALDI TOF and the susceptibility patterns were tested using Microscan according to CLSI guidelines. PCR assays were performed to detect the presence of different VFs (fimH gene encoding for type 1 fimbriae, afaBC for A fimbriae, sfaDE for S fimbriae, KpsMTII for capsule, hlyA for haemolysin A, hlyD for haemolysin D, and cnf-1 for tumor necrosis factor), the phylogenetic groups (PG) A, B1, B2, and D, and the extended spectrum beta-lactamases (ESBLs) genes. Results. The 787 CA-UPEC strains were isolated predominantly from female patients (90.95%) of >30 years (~74%). The resistance rates were 47.52% for ampicillin, 41.16% for tetracycline, 24.39% for cotrimoxazole, 19.18% for amoxicillin-clavulanic acid, 15.50% for cefazolin, 14.99% for ciprofloxacin, and 14.86% for levofloxacin; 35.19% of the investigated strains were MDR and 9.03% ESBL producers (from which 42.25% were positive for blaCTX-M, 38.02% for blaTEM, and 19.71% for blaSHV). FimH was the most frequent virulence gene (93.90%) followed by hlyD (44.34%); afaBC (38.24%); KpsMTII (32.65%); sfaDE (23.88%); hlyA (12.45%); and cnf-1 (7.75%). The distribution of the analyzed UPEC strains in phylogenetic groups was different for non-MDR and MDR strains. Overall, 35% of the strains belonged to the phylogenetic group B2 (harboring the yjaA gene); 27% to group B1 (confirmed by the presence of the TspE4C2 fragment); 16% to group D; and 22% to group A. The CA-UPEC strains included in PG B1 and PG B2 proved to be the most virulent ones, the number of strains carrying multiple VFs (>3) being significantly larger as compared to strains belonging to PG A and PG D) (p90% harbored the fimH gene. High MDR resistance rates were observed, as well as extended VF profiles, highlighting the importance of this type of studies for improving the epidemiological surveillance and the therapeutic or prophylactic management of the respective infections, in the context of antibiotic resistance emergence.

Antimicrobial resistance is one of the most important public health issues. Besides classical multidrug resistance species associated with medical care involved in superficial or invasive infections, there are strains less commonly associated with hospital or outpatient setting’s infections. Non-diphtheria Corynebacterium spp. could produce infections in patients with or without immune-compromised status. The aim of our study was to determine the susceptibility to antimicrobial agents to Corynebacterium spp. from clinical samples collected from Romanian hospitalized individuals and outpatients. Twenty Corynebacterium strains were isolated and identified as Corynebacterium striatum (n = 7), Corynebacterium amycolatum (n = 7), C. urealyticum (n = 3), Corynebacterium afermentans (n = 2), and Corynebacterium pseudodiphtheriticum (n = 1). All isolates have been tested for antibiotic susceptibility by standardized disc diffusion method and minimal inhibitory concentration (MIC) tests. Seventeen isolates demonstrated multidrug resistance phenotypes. The molecular support responsible for high resistance to quinolones for ten of these strains was determined by the detection of point mutation in the gene sequence gyrA.