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The World Health Organization has recently published a list of 12 drug-resistant bacteria that posed a significant threat to human health, and Pseudomonas aeruginosa (P. aeruginosa) was among them. In China, P. aeruginosa is a common pathogen in hospital acquired pneumonia, accounting for 16.9–22.0%. It is a ubiquitous opportunistic pathogen that can infect individuals with weakened immune systems, leading to hospital-acquired acute and systemic infections. The excessive use of antibiotics has led to the development of various mechanisms in P. aeruginosa to resist conventional drugs. Thus, there is an emergence of multidrug-resistant strains, posing a major challenge to conventional antibiotics and therapeutic approaches. Antimicrobial peptides are an integral component of host defense and have been found in many living organisms. Most antimicrobial peptides are characterized by negligible host toxicity and low resistance rates, making them become promising for use as antimicrobial products. This review particularly focuses on summarizing the inhibitory activity of natural antimicrobial peptides against P. aeruginosa planktonic cells and biofilms, as well as the drug interactions when these peptides used in combination with conventional antibiotics. Moreover, the underlying mechanism of these antimicrobial peptides against P. aeruginosa strains was mainly related to destroy the membrane structure through interacting with LPS or increasing ROS levels, or targeting cellular components, leaded to cell lysis. Hopefully, this analysis will provide valuable experimental data on developing novel compounds to combat P. aeruginosa.

In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing–partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (Rp) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse’s sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.

Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core–shell Au@AgNPs. Then, the core–shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 × 10−11 mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky–Golay combined with competitive adaptive reweighted sampling–partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.

Tea plants absorb chromium-contaminated soil and water and accumulate in tea leaves. Hexavalent chromium (Cr6+) is a very toxic heavy metal; excessive intake of tea containing Cr6+ can cause serious harm to human health. A reliable and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed using Au@Ag nanoparticles as an enhanced substrate for the determination of Cr6+ in tea. The Au@AgNPs coated with carbimazole showed a highly selective reaction to Cr6+ in tea samples through a redox reaction between Cr6+ and carbimazole. The Cr6+ in the contaminated tea sample reacted with methimazole—the hydrolysate of carbimazole—to form disulfide, which led to the decrease in the Raman intensity of the peak at 595 cm−1. The logarithm of the concentration of Cr6+ has a linear relationship with the Raman intensity at the characteristic peak and showed a limit of detection of 0.945 mg/kg for the tea sample. The carbimazole functionalized Au@AgNPs showed high selectivity in analyzing Cr6+ in tea samples, even in the presence of other metal ions. The SERS detection technique established in this study also showed comparable results with the standard ICP-MS method, indicating the applicability of the established technique in practical applications.

Cancer stem cells, a relatively small group of self-renewing cancer cells, were first isolated from acute myeloid leukemia. These cells can play a crucial role in tumor metastasis, relapse, and therapy resistance. The cancer stem cell theory may be applied to lung cancer and explain the inefficiency of traditional treatments and eventual recurrence. However, because of the unclear accuracy and illusive biological function of cancer stem cells, some researchers remain cautious about this theory. Despite the ongoing controversy, cancer stem cells are still being investigated, and their biomarkers are being discovered for application in cancer diagnosis, targeted therapy, and prognosis prediction. Potential lung cancer stem cell markers mainly include surface biomarkers such as CD44, CD133, epithelial cell adhesion molecule, and ATP-binding cassette subfamily G member 2, along with intracellular biomarkers such as aldehyde dehydrogenase, sex-determining region Y-box 2, NANOG, and octamer-binding transcription factor 4. These markers have different structures and functions but are closely associated with the stem potential and uncontrollable proliferation of tumor cells. The aberrant activation of major signaling pathways, such as Notch, Hedgehog, and Wnt, may be associated with the expression and regulation of certain lung cancer stem cell markers, thus leading to lung cancer stem cell maintenance, chemotherapy resistance, and cancer promotion. Treatments targeting lung cancer stem cell markers, including antibody drugs, nanoparticle drugs, chimeric antigen receptor T-cell therapy, and other natural or synthetic specific inhibitors, may provide new hope for patients who are resistant to conventional lung cancer therapies. This review provides comprehensive and updated data on lung cancer stem cell markers with regard to their structures, functions, signaling pathways, and promising therapeutic target approaches, aiming to elucidate potential new therapies for lung cancer.

Cervical cancer is one of the most common gynecological tumors, and the majority of early-stage cervical cancer patients achieve good recovery through surgical treatment and concurrent chemoradiotherapy (CCRT). However, for patients with recurrent, persistent, metastatic cervical cancer, effective treatment is rare, except for bevacizumab combined with chemotherapy. Programmed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) inhibitors might be a novel choice to improve the clinical outcomes of these patients. Thus far, some pivotal trials, including Keynote 028, Keynote 158 and Checkmate 358, have indicated established clinical benefit of PD-1/PD-L1 inhibitors in cervical cancer. In light of these data, the FDA has approved pembrolizumab for patients with recurrent or metastatic cervical cancer with disease progression during or after chemotherapy. There are also some ongoing studies that may provide more evidence for the PD-1/PD-L1 pathway as a therapeutic target in cervical cancer. In this review, we have summarized the status and application of PD-1/PD-L1 inhibitors in clinical trials for the treatment of cervical cancer and suggested some future directions in this field.

Infrared (IR) radiometry technology is an important method for characterizing the IR signature of targets, such as aircrafts or rockets. However, the received signal of targets could be reduced by a combination of atmospheric molecule absorption and aerosol scattering. Therefore, atmospheric correction is a requisite step for obtaining the real radiance of targets. Conventionally, the atmospheric transmittance and the air path radiance are calculated by an atmospheric radiative transfer calculation software. In this paper, an improved IR radiometric method based on constant reference correction of atmospheric attenuation is proposed. The basic principle and procedure of this method are introduced, and then the linear model of high-speed calibration in consideration of the integration time is employed and confirmed, which is then applicable in various complex conditions. To eliminate stochastic errors, radiometric experiments were conducted for multiple integration times. Finally, several experiments were performed on a mid-wave IR system with Φ600 mm aperture. The radiometry results indicate that the radiation inversion precision of the novel method is 4.78–4.89%, while the precision of the conventional method is 10.86–13.81%.

Objective Several laboratory and imaging assays are required to diagnose multiple myeloma (MM). Serum and urine immunofixation electrophoresis are two key assays to diagnose MM, while they have not been extensively utilized in Chinese hospitals. Serum light chain (sLC), β2 microglobulin (β2-MG), lactic dehydrogenase (LDH), and immunoglobulin (Ig) are routinely measured in the majority of Chinese hospitals. Imbalance of sLC ratio (involved light chain/uninvolved light chain) is frequently observed in MM patients. This study aimed to evaluate the screening value of sLC ratio, β2-MG, LDH, and Ig in MM patients using receiver operating characteristic (ROC) curves. Methods Data of 303 suspected MM patients, who were admitted to the Taizhou Central Hospital between March 2015 and July 2021, were retrospectively analyzed. In total, 69 patients (MM arm) met the International Myeloma Working Group (IMWG) updated criteria for the diagnosis of MM, while 234 patients were non-MM (non-MM arm). All patients’ sLC, β2-MG, LDH, and Ig were measured using commercially available kits according to the manufacturer’s instructions. The ROC curve analysis was employed to assess the screening value of sLC ratio, β2-MG, LDH, creatinine (Cr) and Ig. The statistical analysis was carried out by SPSS 26.0 (IBM, Armonk, NY, USA) and MedCalc 19.0.4 (Ostend, Belgium) software. Results There was no significant difference between the MM and non-MM arms in terms of gender, age and Cr. The median sLC ratio in the MM arm was 11.5333, which was significantly higher than that of 1.9293 in the non-MM arm (PConclusion The triple combination strategy (sLC ratio, 3.2121; β2-MG, 1.95 mg/L; Ig, 46.4 g/L) is accompanied by remarkable sensitivity and specificity for screening MM in Chinese hospitals.

The aims of this study were to (a) identify the trajectory of symptom clusters in patients with inflammatory bowel disease up to 28 weeks after initiation of infliximab therapy and (b) examine the illness perceptions associated with symptom cluster trajectories. This was a prospective study where participants completed the symptom cluster scale at baseline, 14 weeks, and 28 weeks. A latent growth mixture modeling was used to identify trajectories of symptom clusters that were predicted, using baseline covariates (Brief Illness Perception Questionnaire). A total of 206 patients were included and identified as three latent classes: moderate symptom cluster-stable decline group (C1), high symptom cluster-rapid decline group (C2), and stable symptom cluster-stable trend group (C3). C1 was predicted by cognitive illness perceptions (odds ratio [95% confidence interval]: 1.134 [1.071, 1.200], p < .001). C2 was also predicted by cognitive and emotional illness perceptions (odds ratio [95% confidence interval]: 1.169 [1.095, 1.248], p < .001; odds ratio [95% confidence interval]: 1.174 [1.038, 1.328], p = .011). Patients with inflammatory bowel disease, initiating infliximab therapy, had different symptom cluster trajectories. Illness perceptions were associated with symptom cluster classes, which underline the complexity of symptoms. Paying attention to these factors and providing necessary knowledge and psychological supporting care after infliximab therapy would effectively improve patients' symptom burden., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Society of Gastroenterology Nurses and Associates.)