Skin fungi play an important role in human health. Particulate matter (PM), the main haze pollutant, has been a public environmental threat.

Klebsiella pneumoniae , particularly carbapenem-resistant Klebsiella pneumoniae (CRKP), has emerged as a pressing threat to global public health. Its intrinsic multidrug resistance and hypervirulence collectively pose a dual burden to clinical management. This study used the modified carbapenem inactivation method (mCIM) and microbroth dilution method to analyze the 225 clinical isolates’ antimicrobial resistance phenotypes to characterize the clinical epidemiology, antimicrobial resistance spectrum, and virulence-associated phenotypes of CRKP isolates in the northern Henan region, which were primarily obtained from intensive care units (ICUs, 51.11%) and sputum specimens (71.56%), with the majority of affected patients aged 60 years or older (61.78%). They exhibited high resistance to β-lactam antibiotics, including imipenem (100%) and meropenem (99.55%), while remaining susceptible to tigecycline (resistance rate of 0.88%). Meanwhile, bla _CTX-M and bla _KPC were the predominant resistance-associated genes, whereas rmpA2 , iucA , peg , and rmpA served as key virulence-associated markers for hypervirulent CRKP (hv-CRKP). Notably, hv-CRKP showed a significant negative correlation with resistance gene carriage rates ( P < 0.05) and a significant positive correlation with the hypermucoviscous phenotype ( P < 0.01). CRKP strains in the northern Henan region exhibit concurrent high-level drug resistance and hypervirulence, with a prevalence of hypervirulent CRKP (hv-CRKP). IMPORTANCE: Among the prevalent CRKP strains in Northern Henan, the detection rate of hv-CRKP is relatively high. Moreover, the high-mucus phenotype strains are positively correlated with the virulence gene cluster and negatively correlated with the drug resistance gene load. An analysis framework of “drug resistance gene profile–virulence phenotype–molecular association” is necessary to fill the gap in regional research and to provide key data support for building a three-level drug-resistant bacteria prevention and control system across the “national–regional–hospital” levels.

Background and objectives: Liver metastases are associated with a poor prognosis in gastroesophageal junction (GEJ) cancer patients. The high rate of liver involvement is attributed to the unique anatomical location of the GEJ, which is close to the liver. Patients with liver metastasis typically have advanced, unresectable disease and limited treatment options. Therefore, early detection and prediction are crucial to guide appropriate treatment planning and improve the outcomes for patients with GEJ cancer at risk of liver metastases. Using data from the Surveillance, Epidemiology, and End Results (SEER) database, the present study aimed to elucidate the incidence and risk factors of liver metastases in GEJ cancer patients diagnosed between 2010 and 2019. Methods: This research employed univariable and multivariable logistic regression models to identify risk factors for the development of liver metastases. A predictive nomogram for liver metastases was developed and assessed. Patients' overall survival (OS) with liver metastases was analyzed using the Kaplan-Meier method. Results: The study included 1,322 eligible patients with GEJ cancer, 181 (13.6%) of whom were diagnosed with liver metastases. The median overall survival (mOS) for patients with liver metastasis was approximately eight months, compared to a shorter mOS for patients without liver metastasis (P < 0.001). Factors significantly associated with the occurrence of liver metastasis included N3 stage (OR: 1.84; 95% CI: (1.13-2.96); P < 0.001), surgery (OR: 0.09; 95% CI: (0.06-0.14); P < 0.001), lung metastasis (OR: 2.88; 95% CI: (1.78-4.63); P < 0.001), chemotherapy (OR: 0.54; 95% CI: (0.32-0.87); P < 0.001), and radiation therapy (OR: 0.33; 95% CI: (0.25-0.45); P < 0.001). The nomogram demonstrated good performance in predicting liver metastases in GEJ cancer patients (c-index: 0.820). Conclusions: The study identified lymph node status, surgical, lung metastasis, chemotherapy, and radiation as important predictors of outcomes for patients with GEJ cancer. The developed nomogram might be a valuable tool for predicting the risk of liver metastases in GEJ cancer patients, potentially enhancing clinical decision-making processes. By predicting the risk of liver metastasis occurrence, clinicians might intervene in patients with GEJ cancers as early as possible.