Antimicrobial resistance (AMR) is a major threat to global public health. The current review synthesizes to address the possible role of Artificial Intelligence and Machine Learning (AI/ML) in mitigating AMR. Supervised learning, unsupervised learning, deep learning, reinforcement learning, and natural language processing are some of the main tools used in this domain. AI/ML models can use various data sources, such as clinical information, genomic sequences, microbiome insights, and epidemiological data for predicting AMR outbreaks. Although AI/ML are relatively new fields, numerous case studies offer substantial evidence of their successful application in predicting AMR outbreaks with greater accuracy. These models can provide insights into the discovery of novel antimicrobials, the repurposing of existing drugs, and combination therapy through the analysis of their molecular structures. In addition, AI-based clinical decision support systems in real-time guide healthcare professionals to improve prescribing of antibiotics. The review also outlines how can AI improve AMR surveillance, analyze resistance trends, and enable early outbreak identification. Challenges, such as ethical considerations, data privacy, and model biases exist, however, the continuous development of novel methodologies enables AI/ML to play a significant role in combating AMR.

Background: Aspergillus, a widespread fungus in the natural environment, poses a significant threat to human health by entering the human body via the airways and causing a disease called aspergillosis. This study comprehensively analyzed data on aspergillosis in published articles from mainland China to investigate the prevalence of Aspergillus, and risk factors, mortality rate, and underlying condition associated with aspergillosis. Methods: Published articles were retrieved from Google Scholar, PubMed, and Science Direct online search engines. In the 101 analyzed studies, 3558 Aspergillus isolates were meticulously collected and classified. GraphPad Prism 8 was used to statistically examine the epidemiology and clinical characteristics of aspergillosis. Results: Aspergillus fumigatus was prominently reported ( n = 2679, 75.14%), followed by A. flavus ( n = 437, 12.25%), A. niger ( n = 219, 6.14%), and A. terreus ( n = 119, 3.33%). Of a total of 9810 patients, 7513 probable cases accounted for the highest number, followed by confirmed cases ( n = 1956) and possible cases ( n = 341). In patients, cough emerged as the most common complaint ( n = 1819, 18.54%), followed by asthma ( n = 1029, 10.48%) and fever (1024, 10.44%). Of total studies, invasive pulmonary aspergillosis (IPA) was reported in 47 (45.53%) studies, exhibiting an increased prevalence in Beijing ( n = 12, 25.53%), Guangdong ( n = 7, 14.89%), and Shanghai ( n = 6, 12.76%). Chronic pulmonary aspergillosis (CPA) was reported in 14 (13.86%) studies. Among the total of 14 studies, the occurrence of CPA was 5 (35.71%) in Beijing and 3 (21.42%) in Shanghai. Allergic bronchopulmonary aspergillosis (ABPA), was reported at a lower frequency ( n = 8, 7.92%), Guangdong recorded a relatively high number ( n = 3, 37.5%), followed by Beijing ( n = 2, 25.0%), and Shanghai ( n = 1, 12.5%). Percentage of death reported: IPA had the highest rate ( n = 447, 68.87%), followed by CPA ( n = 181, 27.88%) and ABPA ( n = 14, 2.15%). Among the aspergillosis patients, 6220 had underlying conditions, including chronic lung disease ( n = 3765, 60.53%), previous tuberculosis ( n = 416, 6.68%), and organ transplant or organ failure ( n = 648, 10.41%). Aspergillosis was also found in patients using corticosteroid therapy ( n = 622, 10.0%). Conclusion: This review sheds light on the prevalence patterns of Aspergillus species, risk factors of aspergillosis, and gaps in surveillance that could be helpful for the control and treatment of aspergillosis and guide the researchers in future studies. Registration: This systematic review was prospectively registered on PROSPERO: Registration ID CRD42023476870.

The New Delhi Metallo-β-lactamase (NDM) is among the most threatening forms of carbapenemases produced by K. pneumoniae, well-known to cause severe worldwide infections. The molecular epidemiology of bla_NDM-1-harboring K. pneumoniae is not well elucidated in Pakistan. Herein, we aim to determine the antibiotics-resistance profile, genes type, molecular type, and plasmid analysis of 125 clinically isolated K. pneumoniae strains from urine samples during July 2018 to January 2019 in Pakistan. A total of 34 (27.2%) K. pneumoniae isolates were carbapenemases producers, and 23 (18.4%) harbored the bla_NDM-1 gene. The other carbapenemases encoding genes, i.e., bla_IMP-1 (7.2%), bla_VIM-1 (3.2%), and bla_OXA-48 (2.4%) were also detected. The Multi Locus Sequence Typing (MLST) results revealed that all bla_NDM-1-harboring isolates were ST11. The other sequence types detected were ST1, ST37, and ST105. The cluster analysis of Xbal Pulsed Field Gel Electrophoresis (PFGE) revealed variation amongst the clusters of the identical sequence type isolates. The bla_NDM-1 gene in all of the isolates was located on a 45-kb IncX3 plasmid, successfully transconjugated. For the first time, bla_NDM-1-bearing IncX3 plasmids were identified from Pakistan, and this might be a new primary vehicle for disseminating bla_NDM-1 in Enterobacteriaceae as it has a high rate of transferability.

Candidiasis poses a significant threat to human health, especially in immunocompromised patients. However, there is a paucity of epidemiological data concerning the prevalence of candidiasis in developing regions of China. We conducted a retrospective study on patients positive for Candida infections in a tertiary care hospital in Shantou, China, to identify the clinical characteristics and risk factors for candidiasis. Of 5,095 cases of candidiasis, 489 (9.59%) were candidemia infections. Candida albicans (n = 230, 47.0%) was the predominant species identified among all patients. Non-albicans Candida (NAC) was more prevalent in adult patients, while Candida glabrata was slightly more frequent in pediatric patients (n = 10, 14.7%). Pulmonary diseases (n = 200, 47.8%) were the most common underlying comorbidities in adult patients (n = 25, 35.2%). Thrombocytopenia was the only laboratory finding higher in adult patients than in pediatric patients. Respiratory dysfunction, the presence of a central venous catheter, septic shock, and thrombocytopenia were independent risk factors for candidemia-related 30-day mortality. Amphotericin B exhibited high efficacy (100%), and itraconazole exhibited the lowest efficacy against all tested Candida isolates. C. glabrata had a lower susceptibility to azole, although this was not statistically significant. The epidemiological data on candidiasis, specifically candidemia in pediatric and adult patients, varied regarding the prevalence of Candida species and associated risk factors. This study provides guidance for prescribing the appropriate therapy and yields insights into the susceptibility patterns of different Candida isolates to antifungal drugs.

Fungal dysbiosis is increasingly recognized as a key factor in cancer, influencing tumor initiation, progression, and treatment outcomes. This review explores the role of fungi in carcinogenesis, with a focus on mechanisms such as immunomodulation, inflammation induction, tumor microenvironment remodeling, and interkingdom interactions. Fungal metabolites are involved in oncogenesis, and antifungals can interact with anticancer drugs, including eliciting potential adverse effects and influencing immune responses. Furthermore, mycobiota profiles have potential as diagnostic and prognostic biomarkers, emphasizing their clinical relevance. The interplay between fungi and cancer therapies can affect drug resistance, therapeutic efficacy, and risk of invasive fungal infections associated with targeted therapies. Finally, emerging strategies for modulating mycobiota in cancer care are promising approaches to improve patient outcomes.

Background: Wound infections caused by antimicrobial-resistant bacteria challenge treatment and infection control, particularly in healthcare settings of underdeveloped regions, such as Shantou. Methods: This retrospective study analyzed bacterial spectrum and antimicrobial resistance patterns of wound isolates collected from January 2015 to December 2023 at the Skin and Venereal Disease Prevention and Control Hospital, Shantou, China. Patient data (type, age, sex, infection site) were extracted independently by two researchers. Bacteria were identified using the MALDI Biotyper System or VITEK 2 COMPACT System. Data were analyzed with GraphPad Prism 8.0.2, using the chi-square test for comparisons; p < 0.05 was considered statistically significant. Results: A total of 790 wound specimens were processed using standard microbiological techniques. Staphylococcus aureus was the most prevalent pathogen (39.4%), followed by Klebsiella pneumoniae (12.4%), Pseudomonas aeruginosa (6.89%), Staphylococcus haemolyticus (6.21%), Staphylococcus epidermidis (5.88%) and Escherichia coli (5.21%). Of these, male patients accounted for 363 of 420 (86.4%) cases, more than females, who accounted for 232 of 370 (62.7%). The highest incidence occurred in the 2– 17-year age group (25.0%), followed by those aged 51– 60 years (14.9%). Extended-spectrum β-lactamase (ESBL) production was noted in 41.9% of E. coli and 29.7% of K. pneumoniae. Among the Gram-positive multidrug-resistant (MDR) isolates, S. haemolyticus (91.8%), S. epidermidis (91.4%), and S. aureus (73.9%) were the most resistant. Methicillin-resistant Staphylococcus aureus (MRSA) accounted for 68.5% of S. aureus, with high resistance to penicillin (97.3%) and erythromycin (73.5%). MR-CoNS, mainly S. epidermidis, was resistant to erythromycin (88.5%) and oxacillin (77.1%). Conclusion: The high prevalence of MRSA (68.5%) and MDR S. aureus (73.6%) may reflect widespread antibiotic misuse, emphasizing the need for culture-guided therapy and robust antibiotic stewardship.