Search Results (274)

Background: Bimekizumab, secukinumab, and ixekizumab are IL-17-targeting biologics approved for the treatment of moderate-to-severe plaque psoriasis. While secukinumab and ixekizumab selectively inhibit IL-17A, bimekizumab targets both IL-17A and IL-17F, potentially providing greater anti-inflammatory efficacy. This study aimed to compare the real-world effectiveness, safety, and tolerability of these agents in a Polish dermatology center between 2019 and 2024. Methods: We conducted a retrospective analysis of 98 patients meeting at least one of the following criteria: PASI ≥ 10, BSA ≥ 10, DLQI ≥ 10, or involvement of special areas with inadequate response or contraindications to ≥2 systemic therapies. Patients with prior exposure only to IL-17 inhibitors were excluded. PASI, BSA, and DLQI scores were recorded at baseline, week 4, and week 12. Due to differences in dosing schedules, outcomes were aligned using standardized timepoints and exponential modeling of continuous response trajectories. Mixed-effects ANOVA was used to assess the influence of baseline factors (age, BMI, PsA status) on treatment outcomes. Adverse events were documented at each monthly follow-up visit. Results: Bimekizumab showed the greatest effect size for PASI reduction (Hedges’ g = 3.662), followed by secukinumab (2.813) and ixekizumab (1.986). Exponential modeling revealed a steeper response trajectory with bimekizumab (intercept = 0.289), suggesting a more rapid PASI improvement. The efficacy of bimekizumab was particularly notable in patients who were previously treated with IL-23 inhibitors. All three agents demonstrated favorable safety profiles, with no serious adverse events or discontinuations. The most frequent adverse events were mild and included upper respiratory tract infections and oral candidiasis. Conclusions: This real-world analysis confirmed that IL-17 inhibitors effectively improved PASI, BSA, and DLQI scores in moderate-to-severe psoriasis. Bimekizumab demonstrated the most rapid early improvements and a higher modeled likelihood of complete clearance, without significant differences at week 12. All agents were well tolerated, underscoring the need for further individualized, large-scale studies. Full article

Schizophrenia is a challenging multifactorial neuropsychiatric disease that involves interactions between genetic susceptibility and environmental insults. Increasing evidence implicates viral infections as significant environmental contributors, particularly during sensitive neurodevelopmental periods. This review synthesises current findings on the viral hypothesis of schizophrenia, encompassing a wide array of neurotropic viruses, including influenza viruses, herpesviruses (HSV-1 and 2, CMV, VZV, EBV, HHV-6 and 8), hepatitis B and C viruses, HIV, HERVs, HTLV, Zika virus, BoDV, coronaviruses (including SARS-CoV-2), and others. These pathogens can contribute to schizophrenia through mechanisms such as direct microinvasion, persistent central nervous system infection, immune-mediated neuroinflammation, molecular mimicry, and the disturbance of the blood–brain barrier. Prenatal exposure to viral infections can trigger maternal immune activation, resulting in cytokine-mediated alterations in the neurological development of the foetus that persist into adulthood. Genetic studies highlight the role of immune-related loci, including major histocompatibility complex polymorphisms, in modulating susceptibility to infection and neurodevelopmental outcomes. Clinical data also support the “mild encephalitis” hypothesis, suggesting that a subset of schizophrenia cases involve low-grade chronic neuroinflammation. Although antipsychotics have some immunomodulatory effects, adjunctive anti-inflammatory therapies show promise, particularly in treatment-resistant cases. Despite compelling associations, pathogen-specific links remain inconsistent, emphasising the need for longitudinal studies and integrative approaches such as viromics to unravel causal relationships. This review supports a “multi-hit” model in which viral infections interfere with hereditary and immunological susceptibilities, enhancing schizophrenia risk. Elucidating these virus–immune–brain interactions may facilitate the discovery of biomarkers, targeted prevention, and novel therapeutic strategies for schizophrenia. Full article

Background: Dyslipidemia and schistosomiasis are major public health challenges, particularly in endemic regions where their coexistence may influence host metabolism and immune responses. This study aimed to evaluate visceral adipose tissue (AT) remodeling in a murine model of acute Schistosoma mansoni infection combined with diet-induced dyslipidemia. Methodology: Female Swiss Webster mice were fed either a standard or high-fat diet (HFD) for 29 weeks and infected with S. mansoni at week 20. Nine weeks after infection, biochemical, morphometric, histopathological, and immunological analyses were performed. Results: The HFD promoted weight gain and dyslipidemia, while S. mansoni infection alone did not alter lipid profiles but partially mitigated the metabolic effects of the HFD. Morphometric analysis revealed adipocyte hypertrophy and reduced cell number in HFD-fed animals. In HFD-fed infected mice, infection partially reversed hypertrophy, suggesting a modulatory effect on AT remodeling. Histopathological examinations showed that while a HFD induced mild inflammation, infection led to intense leukocyte infiltration, hyperemia, and plasma cell degeneration. Peritoneal lavage confirmed a proinflammatory immune profile. Conclusions: These findings indicate that the interaction between a HFD and S. mansoni infection exacerbates adipose tissue inflammation and metabolic alterations, highlighting the complex interplay between parasitic infection, diet, and immune-metabolic regulation. Full article

The objective of this study was to evaluate the effects of feeding a combination of chicory–plantain silage and supplementing Se yeast on the response of early-lactating ewes to induce subclinical mastitis. Polypay ewes (n = 32) were fed either chicory–plantain silage or grass silage and supplemented with 3.6 mg Se yeast/ewe/day for approximately 2 months prior to the infusion of S. uberis into both mammary glands (i.e., intramammary infection or IMI). The ewes had a typical subclinical mastitis response with an 8-fold increase in milk somatic cell count within 24 h post-IMI, a decrease in milk yield, and changes in all milk components measured. The ewes experienced a mild systemic inflammation post-IMI as determined by an increase in rectal temperature and decrease in feed and water intake and, in blood, by an increase in the concentration of ceruloplasmin, haptoglobin, and myeloperoxidase and a decrease in paraoxonase, Zn, advanced oxidation protein products, and hematocrit with no effect on pro-inflammatory cytokines. No effect of silage type, likely due to a low concentration of secondary compounds, or Se supplementation was detected in response to IMI. In summary, the subclinical mastitis model used was effective in mounting an inflammatory response, although this was mild; however, feeding chicory–plantain silage with a low concentration of secondary compounds and supplementing Se yeast had no significant effect on the response of ewes to mammary infection. Full article

Background: The long-term impact of SARS-CoV-2 infection on pulmonary function remains insufficiently characterised, particularly among individuals who have experienced mild or asymptomatic disease. This study aimed to assess spirometric changes over a three-year period and evaluate potential associations with demographic and clinical variables. Methods: We retrospectively analysed spirometry data from 103 healthcare workers (HCWs) who underwent pulmonary function tests at three time points: before the pandemic (Time 0), one year post-pandemic (Time 1), and two years post-pandemic (Time 2). Linear regression models were employed to evaluate the impact of various factors, including age, BMI, gender, smoking status, history of SARS-CoV-2 infection, vaccination status prior to infection, and the number of infections, on changes in FVC and FEV₁. Results: A statistically significant decrease in both FVC and FEV₁ were observed at Time 1 and Time 2 compared to baseline (p < 0.05). Smoking habits were significantly associated with a greater decline in both FVC and FEV₁. Multiple infections were associated with larger reductions in FVC at Time 1. No significant associations were found with age, gender, BMI, or vaccination status. Even in the absence of severe symptoms of the disease, healthcare workers exhibited a measurable decline in pulmonary function over time. Smoking and reinfection emerged as relevant factors associated with reduced lung capacity. Conclusions: These findings emphasise the need for ongoing respiratory monitoring in occupational settings and the importance of targeted preventive measures. Full article

Background/Objectives: Acute pancreatitis (AP) is an illness that requires prompt diagnosis and treatment since it has the potential to become life-threatening. The American College of Gastroenterology 2024 (ACG24) guidelines offer a framework for diagnosis, severity, and treatment criteria. To assess Google Gemini application of ACG24 guidelines to Medical Information Mart for Intensive Care-III AP cases for risk, nutrition, and complication management. Methods: This observational cross-sectional study was based on 512 patients with AP who were treated in the Medical Information Mart for Intensive Care-III database from 2001 to 2012. The study compared the efficiency of Gemini in relation to the ACG24 guidelines in the three main areas of risk stratification, enteral nutrition timing, and necrotizing pancreatitis management. Enteral nutrition, according to the ACG24 guidelines, should be started within 48 h for patients who are capable, and antibiotics should only be used for confirmed infected necrosis. Results: The study included 512 patients who were divided into two groups: 213 patients with mild pancreatitis (41.6%) and 299 patients with severe pancreatitis (58.4%). The model achieved 85% accuracy for mild cases and 82% accuracy for severe cases of pancreatitis. The Acute Physiology and Chronic Health Evaluation II and Ranson scores matched the predictions of Gemini for both mild cases (p = 0.28 and p = 0.33, respectively) and severe cases (p = 0.31 and p = 0.27, respectively). The recommendations for early enteral nutrition and delayed feeding in mild cases were correct for 78% of patients, but the system suggested oral intake prematurely in 8% of severe cases. The antibiotic guideline compliance reached 82% among 156 patients with necrotizing pancreatitis, and the procedure for draining infected necrosis was correct 85% of the time. Conclusions: The Gemini model achieved 78–85% accuracy in determining pancreatitis severity and adherence to treatment guidelines but showed lower accuracy in nutrition timing compared to other parameters. Core Tip: This study evaluated the Google Gemini model in applying the American College of Gastroenterology 2024 guidelines for acute pancreatitis across 512 Medical Information Mart for Intensive Care-III cases. Results demonstrated 85% accuracy in severity classification, precise prediction of Acute Physiology and Chronic Health Evaluation II and Ranson scores, and 78–85% compliance with nutritional and necrotizing pancreatitis management guidelines. These findings suggest that artificial intelligence-based clinical decision support systems can provide rapid, consistent, and guideline-concordant recommendations, which are particularly valuable in settings with limited specialist expertise. Full article

Group A β-hemolytic Streptococcus (GAS) is a Gram-positive, coccoid-shaped bacterium that tends to grow in chains; it is a non-spore-forming, facultatively anaerobic, catalase-negative, aerobic bacterium. It is known to cause a wide range of infections in children, ranging from mild upper respiratory tract infections, such as pharyngitis, to severe invasive disease. GAS also notably triggers post-infectious immune sequelae, including acute poststreptococcal glomerulonephritis (APSGN), acute rheumatic fever (ARF), and rheumatic heart disease (RHD), which are major health burdens, especially in low-income countries. In this review, we will present the general characteristics of GAS, highlighting its structural and microbiological features. We will also discuss its pathogenetic mechanisms, especially molecular mimicry, and its ability to cause autoimmune responses. Finally, we will elucidate some of the autoimmune sequelae that mark GAS infections, such as ARF, RHD, APSGN, and guttate psoriasis. Understanding GAS as a model pathogen for infection-induced autoimmunity provides insight into host–pathogen interactions and supports the development of targeted interventions. Emphasis on early diagnosis and antibiotic treatment is essential to reduce the burden of autoimmune complications Full article

With the advancement of modern agricultural technology and the expansion of large-scale production, this article aims to solve the difficulties in plant disease and pest control through the application of artificial intelligence and automation technology, and provide accurate disease and pest warning mechanisms. This study first conducted a detailed identification and classification of plant disease and pest warning mechanisms, and established a dynamic model of disease and pests based on the environmental factors and symptoms of affected areas. On this basis, using the isomorphism relationship between generalized stochastic Petri nets and Markov chains, a plant disease and pest diagnosis model based on generalized stochastic Petri nets and an equivalent Markov chain model were constructed. The simulation results show that different combinations of infection rates have a significant impact on the probability of meeting treatment standards, with the combination of moderate and severe infection rates having the greatest impact on the probability of meeting treatment standards, while the impact of mild infection rates is relatively small. By comprehensively analyzing the interaction between mild, moderate, and severe infection rates, the critical zone surface under different disease and pest warning thresholds was obtained. Through actual data verification, the generalized stochastic Petri net model can effectively quantify the dynamic characteristics of disease and pest propagation. Combined with the equivalent analysis of Markov chains, it can provide key thresholds and decision support for disease and pest warning. This method provides a theoretical basis for automated monitoring and precise control of pests and diseases in large-scale agricultural planting, and it has high practical application value. Full article

Background: Long COVID can develop in individuals who have had COVID-19, regardless of the severity of their initial infection or the treatment they received. Several studies have examined the prevalence and manifestation of symptom phenotypes to comprehend the pathophysiological mechanisms associated with these symptoms. Numerous articles outlined specific approaches for multidisciplinary management and treatment of these patients, focusing primarily on those with mild acute illness. The various management models implemented focused on a patient-centered approach, where the specialists were positioned around the patient. On the other hand, the created pathways do not consider the possibility of symptom clusters when determining how to define diagnostic algorithms. Methods: This retrospective longitudinal study took place at the “Fondazione IRCCS Policlinico San Matteo”, Pavia, Italy (SMATTEO) and at the “Ospedale di Cremona”, ASST Cremona, Italy (CREMONA). Information was retrieved from the administrative data warehouse and from two dedicated registries. We included patients discharged with a diagnosis of severe COVID-19, systematically invited for a 3-month follow-up visit. Unsupervised machine learning was used to identify potential patient phenotypes. Results: Three hundred and eighty-two patients were included in these analyses. About one-third of patients were older than 65 years; a quarter were female; more than 80% of patients had multi-morbidities. Diagnoses related to the circulatory system were the most frequent, comprising 46% of cases, followed by endocrinopathies at 20%. PCA (principal component analysis) had no clustering tendency, which was comparable to the PCA plot of a random dataset. The unsupervised machine learning approach confirms these findings. Indeed, while dendrograms for the hierarchical clustering approach may visually indicate some clusters, this is not the case for the PAM method. Notably, most patients were concentrated in one cluster. Conclusions: The extreme heterogeneity of patients affected by post-acute sequelae of SARS-CoV-2 infection (PASC) has not allowed for the identification of specific symptom clusters with the most recent statistical techniques, thus preventing the generation of common diagnostic-therapeutic pathways. Full article

Background/Objectives: Severe acute respiratory syndrome (SARS-CoV-2) has had a profound global impact and continues to represent a health challenge worldwide. The durability of SARS-CoV-2 vaccine responses in pediatric inflammatory bowel disease (PIBD) patients receiving biologic therapies is unknown. This study aimed to quantify SARS-CoV-2 antibody responses post vaccination in these immunosuppressed patients over 12 months. Methods: Prospective study comparing antibody responses against SARS-CoV-2 spike protein at 1, 3, 6, and 12 months in PIBD patients aged 5–18 years treated with anti-tumor necrosis factor alpha (anti-TNF) therapies with or without an immunomodulator (IM) versus vedolizumab. Results: Between 1 May 2021 and 1 May 2022, 194 participants on anti-TNF monotherapy (n = 78), anti-TNF with IM (n = 83), vedolizumab (n = 15), and steroids (n = 18) were recruited. Anti-SARS-CoV-2 spike levels increased after the first vaccine and were further boosted 1 month after the second dose. Linear mixed-effects modelling showed antibody waning over time (effect difference −2509 IgG AU/mL per week [95%CI: −4998–−20, p = 0.048]), counterbalanced by booster doses (effect difference 184,138 IgG AU/mL per additional vaccine dose [95%CI: 138,342–229,934, p < 0.001]). Receiving anti-TNF therapy contributed to reduced antibody responses compared to vedolizumab (anti-TNF monotherapy effect difference: −212,640 [95%CI: −336,928–−88,351] p = 0.001; anti-TNF with IM: −151,880 [95%CI: −277,309–−26,451] p = 0.018). Seroconversion and breakthrough infection rates were similar between groups, and all infections were mild, without hospitalizations. Conclusions: Although SARS-CoV-2 antibody responses were attenuated in PIBD patients receiving anti-TNF therapy compared with vedolizumab, this did not impact protection, as seroconversion and breakthrough infection rates were similar, with no hospitalizations. These data reinforce the importance of updating vaccines and, in particular, SARS-CoV-2 vaccines in immunosuppressed PIBD patients on advanced therapies. Full article

Despite several years passing since the COVID-19 pandemic was declared, challenges remain in understanding the factors that can predict the severity of COVID-19 disease and complications of SARS-CoV-2 infection. While many large-scale multi-omic datasets have been published, integration of these datasets has the potential to substantially increase the biological insight gained, allowing a more complex comprehension of the disease pathogenesis. Such insight may improve our ability to predict disease progression, detect severe cases more rapidly and develop effective therapeutics. In this study, we have applied an innovative machine learning algorithm to delineate COVID severity based on the integration of paired samples of proteomic and transcriptomic data from a small cohort of patients testing positive for SARS-CoV-2 infection with differential disease severity. Targeted plasma proteomics and an onco-immune targeted transcriptomic panel were performed on sequential samples from a cohort of 23 severe, 21 moderate and 10 mild COVID-19 patients. We applied DIABLO, a new integrative method, to identify multi-omics biomarker panels that can discriminate between multiple phenotypic groups, such as the varied severity of disease in COVID-19 patients. As COVID-19 severity is known among our sample group, we can train models using this as the outcome variable and calculate features that are important predictors of severe disease. In this study, we detect highly correlated key variables of severe COVID-19 using transcriptomic discriminant analysis and multi-omics integration methods. This approach highlights the power of data integration from a small cohort of patients, offering a better biological understanding of the molecular mechanisms driving COVID-19 severity and an opportunity to improve the prediction of disease trajectories and targeted therapeutics. Full article

Background/Objectives: Hydroxybisphosphonate-conjugated sitafloxacin (HBCS) was developed to achieve higher antibiotic concentrations within infected bone. Small animal studies supported further development, but the feasibility of HBCS treatment in a more clinically relevant and larger animal model is unknown. Methods: In this study, we present case reports on four sheep, each receiving four MRSA-contaminated tibial screws treated with different regimens of intravenous antibiotics. The first two sheep received two screws contaminated with 10³ CFU and two screws contaminated with 10⁵ CFU. Sheep 1 only received vancomycin, starting on day two. Sheep 2 received vancomycin, starting on day 2, but also received 7 doses of HBCS (2 mg/kg/48 h). The protocol for the final two sheep was revised, and both received four screws contaminated with 10³ CFU, and vancomycin was started preoperatively. Sheep 3 and 4 received 7 doses (starting on day 6) and 9 doses (starting on day 2) of HBCS (4 mg/kg/48 h), respectively. Bacteriology was performed on three screws per animal. Longitudinal radiography and histology (n = 1 screw) were assessed for signs of osteolysis and reactive bone formation. Electron microscopy (EM) was performed in the first two sheep to evaluate antibiotic-induced bacterial damage. Results: All sheep tolerated HBCS infusion without clinical signs of discomfort. In addition to a high bacterial load (~10⁴ CFU on all screws), Sheep 1 displayed extensive radiographic and histologic evidence of peri-implant osteolysis and reactive bone formation. Despite having a high bacterial load (~10⁴ CFU on all screws), Sheep 2 displayed only mild radiographic and histologic evidence of peri-implant osteolysis and periosteal reactive bone formation. Bacteriology in Sheep 3 and 4 demonstrated near MRSA eradication (<100 CFU on 2 screws). Both sheep displayed no evidence of osteolysis or new bone formation adjacent to the screw head. EM confirmed the presence of bacteria resorbing bone and replicating in biofilm in Sheep 1, while antibiotic-killed bacteria with ruptured septal planes were seen in Sheep 2. Conclusions: This study demonstrates the feasibility of HBCS therapy in a clinically relevant animal model and provides guidance on future efficacy studies, such as the use of an inoculum of 10³ CFU per screw, the initiation of antibiotic treatment commencing at the time of surgery, and the usability of antibiotic-killed bacteria within altered glycocalyx observed by TEM as a potential biomarker for HBCS efficacy. Full article

Background/Objectives: Diabetic foot infections (DFIs) are commonly associated with frequent hospitalizations, limb amputations, and premature death due to the profile of the bacteria infecting foot ulcers. DFIs are generally colonized by a polymicrobial net of bacteria that grows in biofilms, developing an increased antimicrobial resistance to multiple antibiotics. DFI treatment is a hurdle, and the need to develop new therapies that do not promote resistance is urgent. Therefore, the antibacterial efficacy of Nisin Z (antimicrobial peptide), a core–shell polycationic polyurea pharmadendrimer (PURE_G4OEI₄₈) (antimicrobial polymer), and amlodipine (antihypertensive drug) was evaluated against S. aureus and P. aeruginosa isolated from a DFI and previously characterized. Methods: The antibacterial activity was analyzed in vitro by determining the minimal inhibitory concentration (MIC) and in vivo in a Galleria mellonella model by assessing the larvae survival and health index. Results: The results indicate that Nisin Z exhibited antibacterial activity against S. aureus in vivo, allowing larvae full survival, and no antibacterial activity against P. aeruginosa. Nisin Z may have reduced the antibacterial effectiveness of both PURE_G4OEI₄₈ and amlodipine. PURE_G4OEI₄₈ significantly increased the survival of the larvae infected with P. aeruginosa, while amlodipine showed no activity against both bacteria in vivo. Conclusions: These findings suggest that both Nisin Z and PURE_G4OEI₄₈ could potentially be used individually as adjunct treatments for mild DFIs. However, further studies are needed to confirm these findings and assess the potential toxicity and efficacy of PURE_G4OEI₄₈ in more complex models. Full article

Streptococcus pneumoniae (pneumococcus) is a significant human pathogen responsible for a range of diseases from mild infections to invasive pneumococcal diseases, particularly affecting children, the elderly, and immunocompromised individuals. Despite pneumococcal conjugate vaccines having reduced disease incidence, challenges persist due to serotype diversity, vaccine coverage gaps, and antibiotic resistance. This review highlights the role of LytA, a key autolysin (N-acetylmuramoyl-l-alanine amidase), in pneumococcal biology. LytA regulates autolysis, contributes to inflammation, and biofilm formation, and impairs bacterial clearance. It also modulates complement activation, aiding immune evasion. LytA expression is influenced by environmental signals and genetic regulation and is tied to competence for genetic transformation, which is an important virulence trait, particularly in meningitis. With the increase in antibiotic resistance, LytA has emerged as a potential therapeutic target. Current research explores its use in bacteriolytic therapies, vaccine development, and synergistic antibiotic strategies. Various compounds, including synthetic peptides, plant extracts, and small molecules, have been investigated for their ability to trigger LytA-mediated bacterial lysis. Future directions include the development of novel anti-pneumococcal interventions leveraging LytA’s properties while overcoming vaccine efficacy and resistance-related challenges. Human challenge models and animal studies continue to deepen our understanding of pneumococcal pathogenesis and potential treatment strategies. Full article

Background/Objectives: Primary obstructive megaureter (POM) is a rare congenital urological condition usually diagnosed prenatally or in early childhood. Conservative management is increasingly preferred due to a high potential for spontaneous resolution. However, reliable predictors of spontaneous resolution remain controversial, complicating clinical decision-making. This study aimed to identify the demographic, clinical, and imaging parameters predictive of spontaneous resolution in patients with primary obstructive megaureter. Methods: We retrospectively analyzed 21 pediatric patients diagnosed with primary obstructive megaureter, who were treated conservatively at the Maria Sklodowska Curie Emergency Clinical Hospital for Children from January 2015 to December 2024. Clinical parameters, imaging findings, and renal function were evaluated. Statistical analyses included univariate comparisons and multivariate logistic regression modeling. Results: Spontaneous resolution occurred in 12 (57%) patients, at a median age of 45.75 months. The only statistically significant predictor identified was the initial hydronephrosis grade (p = 0.046). Patients with mild-to-moderate dilation (Grades I–II) had a significantly higher resolution rate (11 of 15 cases) compared with those with severe dilation (1 of 6 cases). Ureteral diameter showed a trend toward predicting outcomes, with unresolved cases having larger median diameters (15 mm vs. 10.5 mm, p ≈ 0.08). Age at diagnosis, sex, bilateral involvement, and history of urinary infections did not significantly influence resolution rates. Conclusions: The initial severity of hydronephrosis significantly predicts spontaneous resolution in primary obstructive megaureter. Conservative management is particularly justified in mild-to-moderate cases, whereas patients with severe dilation may require early intervention due to lower resolution likelihood. Full article