Prognostic nomograms for predicting long-term overall survival in spindle cell melanoma: a population-based study.

Background: There are few research findings on the survival prognosis of spindle cell melanoma (SCM), which is an unusual kind of melanoma. The purpose of this study was to develop a thorough nomogram for predicting the overall survival (OS) of patients with SCM and to assess its validity by comparing it with the conventional American Joint Committee on Cancer (AJCC) staging system. Methods: The Surveillance, Epidemiology, and End Results database was searched, and 2,015 patients with SCM were selected for the analysis. The patients were randomly divided into training (n = 1,410) and validation (n = 605) cohorts by using R software. Multivariate Cox regression was performed to identify predictive factors. A nomogram was established based on these characteristics to predict OS in SCM. The calibration curve, concordance index (C-index), area under the receiver operating characteristic curve, and decision-curve analysis were utilized to assess the accuracy and reliability of the model. The net reclassification improvement and integrated discrimination improvement were also applied in this model to evaluate its differences with the AJCC model. Results: The developed nomogram suggests that race, AJCC stage, chemotherapy status, regional node examination status, marital status, and sex have the greatest effects on OS in SCM. The nomogram had a higher C-index than the AJCC staging system (0.751 versus 0.633 in the training cohort and 0.747 versus 0.650 in the validation cohort). Calibration plots illustrated that the model was capable of being calibrated. These criteria demonstrated that the nomogram outperforms the AJCC staging system alone. Conclusion: The nomogram developed in this study is sufficiently reliable for forecasting the risk and prognosis of SCM, which may facilitate personalized treatment recommendations in upcoming clinical trials.

Rapid detection of pathogenic fungi from coastal population with respiratory infections using microfluidic chip technology.

BACKGROUND: Currently, culture methods are commonly used in clinical tests to detect pathogenic fungi including Candida spp. Nonetheless, these methods are cumbersome and time-consuming, thereby leading to considerable difficulties in diagnosis of pathogenic fungal infections, especially in situations that respiratory samples such as alveolar lavage fluid and pleural fluid contain extremely small amounts of microorganisms. The aim of this study was to elucidate the utility and practicality of microfluidic chip technology in quick detection of respiratory pathogenic fungi. METHODS: DNAs of clinical samples (mainly derived from sputa, alveolar lavage fluid, and pleural fluid) from 64 coastal patients were quickly detected using microfluidic chip technology with 20 species of fungal spectrum and then validated by Real-time qPCR, and their clinical baseline data were analyzed. RESULTS: Microfluidic chip results showed that 36 cases infected with Candida spp. and 27 cases tested negative for fungi, which was consistent with Real-time qPCR validation. In contrast, only 16 cases of fungal infections were detected by the culture method; however, one of the culture-positive samples tested negative by microfluidic chip and qPCR validation. Moreover, we found that the patients with Candida infections had significantly higher rates of platelet count reduction than fungi-negative controls. When compared with the patients infected with C. albicans alone, the proportion of males in the patients co-infected with multiple Candidas significantly increased, while their platelet counts significantly decreased. CONCLUSIONS: These findings suggest that constant temperature amplification-based microfluidic chip technology combined with routine blood tests can increase the detection speed and accuracy (including sensitivity and specificity) of identifying respiratory pathogenic fungi.

Wogonin induces apoptosis in macrophages by exhibiting cytotoxic and genotoxic effects.

Macrophages play an important role in defending the body against invading pathogens. In the face of pathogens, macrophages become activated and release toxic materials that disrupt the pathogens. Macrophage overactivation can lead to severe illness and inflammation. Wogonin has several therapeutic effects, including anti-inflammatory, anticancer, antioxidant, and neuroprotective effects. No studies have investigated the cytotoxic effects of wogonin at concentrations of more than 0.1 mM in RAW264.7 cells. In this study, RAW 264.7 cells were treated with wogonin, which, at concentrations of more than 0.1 mM, had cytotoxic and genotoxic effects in the RAW264.7 cells, leading to apoptosis and necrosis. Further, wogonin at concentrations of more than 0.1 mM induced caspase-3, caspase-8, and caspase-9 activation and mitochondrial dysfunction and death receptor expression. These results suggest that wogonin induces apoptosis through upstream intrinsic and extrinsic pathways by exhibiting cytotoxic and genotoxic effects.

Cyclizine induces cytotoxicity and apoptosis in macrophages through the extrinsic and intrinsic apoptotic pathways.

Cyclizine, an over-the-counter and prescription antihistamine, finds widespread application in the prevention and treatment of motion sickness, encompassing symptoms such as nausea, vomiting, dizziness, along with its effectiveness in managing vertigo. However, the overuse or misuse of cyclizine may lead to hallucinations, confusion, tachycardia, and hypertension. The molecular mechanisms underlying cyclizine-induced cytotoxicity and apoptosis remain unclear. During the 24 h incubation duration, RAW264.7 macrophages were exposed to different concentrations of cyclizine. Cytotoxicity was assessed through the lactate dehydrogenase assay. Flow cytometry employing annexin V-fluorescein isothiocyanate and propidium iodide was utilized to evaluate apoptosis and necrosis. Caspase activity and mitochondrial dysfunction were evaluated through a fluorogenic substrate assay and JC-1 dye, respectively. Flow cytometry employing fluorogenic antibodies was utilized to evaluate the release of cytochrome c and expression of death receptor, including tumor necrosis factor-α receptor and Fas receptor. Western blotting was utilized to evaluate the expression of the Bcl2 and Bad apoptotic regulatory proteins. The findings unveiled from the present study demonstrated that cyclizine exerted a concentration-dependent effect on RAW264.7 macrophages, leading to the induction of cytotoxicity, apoptosis, and necrosis. This compound further activated the intrinsic apoptotic pathway by inducing mitochondrial dysfunction, Bcl2/Bad exchange expression, cytochrome c liberation, and activation of caspases contained caspase 3, 8, and 9. Moreover, the activation of the extrinsic apoptotic pathway was observed as cyclizine induced the upregulation of death receptors and increased caspase activities. Based on our investigations, it can be inferred that cyclizine prompts cytotoxicity and apoptosis in RAW264.7 macrophages in a concentration-dependent manner by triggering both the intrinsic and extrinsic apoptotic pathways.

Efficacy of Rituximab in the Treatment of Pemphigus Vulgaris: A Meta-analysis.

Background: Pemphigus vulgaris (PV) accounts for about 80% of all patients with pemphigus, and is the type with the most serious condition and the worst prognosis among autoimmune bullous diseases. Glucocorticoid and immunosuppressor are the main treatment method for PV. Methods: The computer retrieves four databases obtain controlled trials on the effects of Rituximab in patients with pemphigus vulgaris. After a rigorous literature quality evaluation, data analysis was performed using RevMan 5.3 software. Results: 7 studies were ultimately included in this meta-analysis. 6 studies reported the Remission rate of the test group and the control group, which was significantly higher (OR:2.26; 95% Cl: 1.80,2.82; P < .01) than the control group. Meta-analysis showed that the improvement of the Recurrence rate was significantly lower than the control group (OR:0.36; 95% Cl: 0.20,0.67; P < .01). Meta-analysis showed that the Adverse reactions was no significant statistical significance than the control group (OR:0.82; 95% Cl: 0.53,1.28; P = .383). Conclusion: The results of this study suggest that Rituximab may be effective in patients with pemphigus vulgaris, which will bring light for patients and doctors. And the above conclusions need to be verified by more high-quality studies.

Competing-risks analysis for evaluating the prognosis of patients with microinvasive cutaneous squamous cell carcinoma based on the SEER database.

BACKGROUND: Utilizing the traditional Cox regression model to identify the factors affecting the risk of mortality due to microinvasive cutaneous squamous cell carcinoma (micSCC) may produce skewed results. Since cause-specific mortality can guide clinical decision-making, this study employed the Fine-Gray model based on the Surveillance, Epidemiology, and End Results (SEER) database to identify significant predictive variables for the risk of micSCC-related mortality. METHODS: This study used the information of patients with micSCC who were listed in the SEER database during 2000-2015. Cox regression and Fine-Gray models were utilized for the multivariable analysis, and Gray's test and the cumulative incidence function were used for the univariable analyses. RESULTS: There were 100 patients who died from other reasons and 38 who died from micSCC among the 1259 qualified patients with micSCC. Most were female, white, married, had localized metastasis, etc. According to the univariable Gray's test (P < 0.05), the cumulative incidence rate for events of interest was strongly associated with age, sex, marital status, American Joint Committee on Cancer staging, radiation status, summary stage, chemotherapy status, surgery status, and tumor size. Multivariable Cox regression analysis and multivariable competing-risks analysis indicated that age, tumor size, and income were independent risk variables for the prognosis of patients with micSCC. In both age and tumor size variables, the competing-risks model showed a slight decrease in the hazard ratio and a slight narrowing of the 95% confidence interval compared with the Cox regression model. However, this pattern is not evident in the income variable. CONCLUSIONS: This study established a Fine-Gray model for identifying the independent risk factors that influence the risk of mortality among patients with micSCC. This study uncovers that, in the context of competing risks, age, tumor size, and income serve as independent risk factors influencing the risk of mortality due to micSCC among patients. Our findings have the potential to provide more accurate risk assessments for patient outcomes and contribute to the development of individualized treatment plans.

Analysis and prediction of 5-year survival in patients with cutaneous melanoma: a model-based period analysis.

Background: The survival and prognosis of patients are significantly threatened by cutaneous melanoma (CM), which is a highly aggressive disease. It is therefore crucial to determine the most recent survival rate of CM. This study used population-based cancer registry data to examine the 5-year relative survival rate of CM in the US. Methods: Period analysis was used to assess the relative survival rate and trends of patients with CM in the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2018. And based on the data stratified by age, gender, race and subtype in the SEER database, a generalized linear model was 12established to predict the 5-year relative survival rate of CM patients from 2019 to 2023. Results: The 5-year relative survival increased to various degrees for both total CM and CM subtypes during the observation period. The improvement was greatest for amelanotic melanoma, increasing from 69.0% to 81.5%. The 5-year overall relative survival rates of CM were 92.9%, 93.5%, and 95.6% for 2004-2008, 2009-2013, and 2014-2018, respectively. Females had a marginally higher survival rate than males for almost all subtypes, older people had lower survival rates than younger people, white patients had higher survival rates than nonwhite ones, and urban locations had higher rates of survival from CM than rural locations did. The survival rate of CM was significantly lower for distant metastasis. Conclusion: The survival rate of patients with CM gradually improved overall during 2004-2018. With the predicted survival rate of 96.7% for 2019-2023, this trend will still be present. Assessing the changes experienced by patients with CM over the previous 15 years can help in predicting the future course of CM. It also provides a scientific foundation that associated departments can use to develop efficient tumor prevention and control strategies.

Deep-learning-based survival prediction of patients with lower limb melanoma.

BACKGROUND: For the purpose to examine lower limb melanoma (LLM) and its long-term survival rate, we used data from the Surveillance, Epidemiology and End Results (SEER) database. To estimate the prognosis of LLM patients and assess its efficacy, we used a powerful deep learning and neural network approach called DeepSurv. METHODS: We gathered data on those who had an LLM diagnosis between 2000 and 2019 from the SEER database. We divided the people into training and testing cohorts at a 7:3 ratio using a random selection technique. To assess the likelihood that LLM patients would survive, we compared the results of the DeepSurv model with those of the Cox proportional-hazards (CoxPH) model. Calibration curves, the time-dependent area under the receiver operating characteristic curve (AUC), and the concordance index (C-index) were all used to assess how accurate the predictions were. RESULTS: In this study, a total of 26,243 LLM patients were enrolled, with 7873 serving as the testing cohort and 18,370 as the training cohort. Significant correlations with age, gender, AJCC stage, chemotherapy status, surgery status, regional lymph node removal and the survival outcomes of LLM patients were found by the CoxPH model. The CoxPH model's C-index was 0.766, which signifies a good degree of predicted accuracy. Additionally, we created the DeepSurv model using the training cohort data, which had a higher C-index of 0.852. In addition to calculating the 3-, 5-, and 8-year AUC values, the predictive performance of both models was evaluated. The equivalent AUC values for the CoxPH model were 0.795, 0.767, and 0.847, respectively. The DeepSurv model, in comparison, had better AUC values of 0.872, 0.858, and 0.847. In comparison to the CoxPH model, the DeepSurv model demonstrated greater prediction performance for LLM patients, as shown by the AUC values and the calibration curve. CONCLUSION: We created the DeepSurv model using LLM patient data from the SEER database, which performed better than the CoxPH model in predicting the survival time of LLM patients.

Proteomics analysis to investigate the potential mechanism of theacrine against UV-induced skin photodamage.

AIM: This study aimed to explore the underlying mechanism of theacrine treatment of UV-induced skin photodamage. MATERIALS AND METHODS: Tandem Mass Tag (TMT) relative quantitative proteomics analysis was used to characterize the proteins and pathways associated with the ability of theacrine to combat photodamage in mouse skin by modeling UV irradiation of the backs of ICR mice. RESULTS: Apoptosis-related proteins and signaling pathways play a key role in the ability of theacrine to protect against skin photodamage, according to proteomic and bioinformatics analysis; molecular docking and Western blotting further revealed that theacrine was associated with apoptosis-related proteins (p53, Bcl-2, Bax, caspase-3, and cleaved-caspase-3) with strong binding affinity, which can significantly reduce skin cell apoptosis induced by UV exposure. CONCLUSION: The findings revealed that theacrine can reduce UVB-induced epidermal damage by controlling the apoptosis signaling pathway, implying that theacrine could be a useful anti-UVB damage agent.

SLC38A5 aggravates DC-mediated psoriasiform skin inflammation via potentiating lysosomal acidification.

Amino acid (aa) metabolism is closely correlated with the pathogenesis of psoriasis; however, details on aa transportation during this process are barely known. Here, we find that SLC38A5, a sodium-dependent neutral aa transporter that counter-transports protons, is markedly upregulated in the psoriatic skin of both human patients and mouse models. SLC38A5 deficiency significantly ameliorates the pathogenesis of psoriasis, indicating a pathogenic role of SLC38A5. Surprisingly, SLC38A5 is almost exclusively expressed in dendritic cells (DCs) when analyzing the psoriatic lesion and mainly locates on the lysosome. Mechanistically, SLC38A5 potentiates lysosomal acidification, which dictates the cleavage and activation of TLR7 with ensuing production of pro-inflammatory cytokines such as interleukin-23 (IL-23) and IL-1ß from DCs and eventually aggravates psoriatic inflammation. In summary, this work uncovers an auxiliary mechanism in driving lysosomal acidification, provides inspiring insights for DC biology and psoriasis etiology, and reveals SLC38A5 as a promising therapeutic target for treating psoriasis.

A prognostic nomogram for the cancer-specific survival of white patients with invasive melanoma at BANS sites based on the Surveillance, Epidemiology, and End Results database.

Objective: The purpose of this study was to develop a comprehensive nomogram for the cancer-specific survival (CSS) of white patients with invasive melanoma at back, posterior arm, posterior neck, and posterior scalp (BANS) sites and to determine the validity of the nomogram by comparing it with the conventional American Joint Committee on Cancer (AJCC) staging system. Methods: This study analyzed the patients with invasive melanoma in the Surveillance, Epidemiology, and End Results (SEER) database. R software was used to randomly divide the patients into training and validation cohorts at a ratio of 7:3. Multivariable Cox regression was used to identify predictive variables. The new survival nomogram was compared with the AJCC prognosis model using the concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), net reclassification index (NRI), integrated discrimination index (IDI), calibration plotting, and decision-curve analysis (DCA). Results: A novel nomogram was established to determine the 3-, 5-, and 8-year CSS probabilities of patients with invasive melanoma. According to the nomogram, the Age at Diagnosis had the greatest influence on CSS in invasive melanoma, followed by Bone Metastasis, AJCC, Stage, Liver Metastasis, Histologic Subtype, Brain Metastasis, Ulceration, and Primary Site. The nomogram had a higher C-index than the AJCC staging system in both the training (0.850 versus 0.799) and validation (0.829 versus 0.783) cohorts. Calibration plotting demonstrated that the model had good calibration ability. The nomogram outperformed the AJCC staging system in terms of AUC, NRI, IDI, and DCA. Conclusion: This was the first study to develop and evaluate a comprehensive nomogram for the CSS of white patients with invasive melanoma at BANS sites using the SEER database. The novel nomogram can assist clinical staff in predicting the 3-, 5-, and 8-year CSS probabilities of patients with invasive melanoma more accurately than can the AJCC staging system.

Crafting a prognostic nomogram for the overall survival rate of cutaneous verrucous carcinoma using the surveillance, epidemiology, and end results database.

Background: The aim of this study was to establish and verify a predictive nomogram for patients with cutaneous verrucous carcinoma (CVC) who will eventually survive and to determine the accuracy of the nomogram relative to the conventional American Joint Committee on Cancer (AJCC) staging system. Methods: Assessments were performed on 1125 patients with CVC between 2004 and 2015, and the results of those examinations were recorded in the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided at a ratio of 7:3 into the training (n = 787) and validation (n = 338) cohorts. Predictors were identified using stepwise regression analysis in the COX regression model for create a nomogram to predict overall survival of CVC patients at 3-, 5-, and 8-years post-diagnosis. We compared the performance of our model with that of the AJCC prognosis model using several evaluation metrics, including C-index, NRI, IDI, AUC, calibration plots, and DCAs. Results: Multivariate risk factors including sex, age at diagnosis, marital status, AJCC stage, radiation status, and surgery status were employed to determine the overall survival (OS) rate (P<0.05). The C-index nomogram performed better than the AJCC staging system variable for both the training (0.737 versus 0.582) and validation cohorts (0.735 versus 0.573), which AUC (> 0.7) revealed that the nomogram exhibited significant discriminative ability. The statistically significant NRI and IDI values at 3-, 5-, and 8-year predictions for overall survival (OS) in the validation cohort (55.72%, 63.71%, and 78.23%, respectively and 13.65%, 20.52%, and 23.73%, respectively) demonstrate that the established nomogram outperforms the AJCC staging system (P < 0.01) in predicting OS for patients with cutaneous verrucous carcinoma (CVC). The calibration plots indicate good performance of the nomogram, while decision curve analyses (DCAs) show that the predictive model could have a favorable clinical impact. Conclusion: This study constructed and validated a nomogram for predicting the prognosis of patients with CVC in the SEER database and assessed it using several variables. This nomogram model can assist clinical staff in making more-accurate predictions than the AJCC staging method about the 3-, 5-, and 8-year OS probabilities of patients with CVC.

Deep-learning-based survival prediction of patients with cutaneous malignant melanoma.

Background: This study obtained data on patients with cutaneous malignant melanoma (CMM) from the Surveillance, Epidemiology, and End Results (SEER) database, and used a deep learning and neural network (DeepSurv) model to predict the survival rate of patients with CMM and evaluate its effectiveness. Methods: We collected information on patients with CMM between 2004 and 2015 from the SEER database. We then randomly divided the patients into training and testing cohorts at a 7:3 ratio. The likelihood that patients with CMM will survive was forecasted using the DeepSurv model, and its results were compared with those of the Cox proportional-hazards (CoxPH) model. The calibration curves, time-dependent area under the receiver operating characteristic curve (AUC), and concordance index (C-index) were used to assess the prediction abilities of the model. Results: This study comprised 37,758 patients with CMM: 26,430 in the training cohort and 11,329 in the testing cohort. The CoxPH model demonstrated that the survival of patients with CMM was significantly influenced by age, sex, marital status, summary stage, surgery, radiotherapy, chemotherapy, postoperative lymph node dissection, tumor size, and tumor extension. The C-index of the CoxPH model was 0.875. We also constructed the DeepSurv model using the data from the training cohort, and its C-index was 0.910. We examined how well the aforementioned two models predicted outcomes. The 1-, 3-, and 5-year AUCs were 0.928, 0.837, and 0.855, respectively, for the CoxPH model, and 0.971, 0.947, and 0.942 for the DeepSurv model. The DeepSurv model presented a greater predictive effect on patients with CMM, and its reliability was better than that of the CoxPH model according to both the AUC value and the calibration curve. Conclusion: The DeepSurv model, which we developed based on the data of patients with CMM in the SEER database, was found to be more effective than the CoxPH model in predicting the survival time of patients with CMM.

A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database.

Introduction: This study aimed to develop and validate a nomogram for predicting cancer-specific survival (CSS) in patients with non-keratinized large cell squamous cell carcinoma (NKLCSCC) at 3, 5, and 8 years after diagnosis. Methods: Data on SCC patients were collected from the Surveillance, Epidemiology, and End Results database. Training (70%) and validation (30%) cohorts were generated using random selection of patients. Independent prognostic factors were selected using the backward stepwise Cox regression model. To predict the CSS rates in patients with NKLCSCC at 3, 5, and 8 years after diagnosis, all of the factors were incorporated into the nomogram. Indicators such as the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration curve, and decision-curve analysis (DCA) were then used to validate the performance of the nomogram. Results: This study included 9,811 patients with NKLCSCC. Twelve prognostic factors were identified by Cox regression analysis in the training cohort, which were age, number of regional nodes examined, number of positive regional nodes, sex, race, marital status, American Joint Committee on Cancer (AJCC) stage, surgery status, chemotherapy status, radiotherapy status, summary stage, and income. The constructed nomogram was validated both internally and externally. The nomogram had good discrimination ability, as indicated by the comparatively high C-indices and AUC values. The nomogram was properly calibrated, as indicated by the calibration curves. Our nomogram was superior to the AJCC model, as illustrated by its superior NRI and IDI values. DCA curves indicated the clinical usability of the nomogram. Conclusion: The first nomogram for prognosis predictions of patients with NKLCSCC has been developed and verified. Its performance and usability demonstrated that the nomogram could be utilized in clinical settings. However, additional external verification is still required.

Prognosis of the Keratinizing Squamous Cell Carcinoma of the Tongue Based on Surveillance, Epidemiology, and End Results Database.

Background: The objective of this study is to determine the prognostic factors of keratinizing squamous cell carcinoma of the tongue (KTSCC) and to establish a prognostic nomogram of KTSCC to assist clinical diagnosis and treatment. Methods: This study identified 3874 patients with KTSCC from the Surveillance, Epidemiology, and End Results (SEER) database, and these patients were randomly divided into the training (70%, (n = 2711) and validation (30%, n = 1163) cohorts. Cox regression was then used to filter variables. Nomograms were then constructed based on meaningful variables. Finally, the concordance index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration charts, and decision-curve analysis (DCA), were used to evaluate the discrimination, accuracy and effectiveness of the model. Results: A nomogram model was established for predicting the 3-, 5-, and 8-year overall survival (OS) probabilities of patients with KTSCC. The model indicated that age, radiotherapy sequence, SEER stage, marital status, tumor size, American Joint Committee on Cancer (AJCC) stage, radiotherapy status, race, lymph node dissection status, and sex were factors influencing the OS of patients with KTSCC. Verified by C-index, NRI, IDI, calibration curve, and DCA curve, our model has better discrimination, calibration, accuracy and net benefit compared to the AJCC system. Conclusions: This study identified the factors that affect the survival of KTSCC patients and established a prognostic nomogram that can help clinicians predict the 3-, 5-, and 8-year survival rates of KTSCC patients.

Effects of low-dose furosemide combined with aminophylline on the renal function in septic shock patients.

BACKGROUND: To investigate the effects of low-dose furosemide and aminophylline on the renal function in patients with septic shock. METHODS AND RESULTS: A total of 109 eligible septic shock patients in the intensive care unit were randomly divided into a control group (n = 55) and an intervention group (n = 54). The control group received normal saline, and the intervention group received low-dose furosemide (0.048 mg/kg.h-1) with aminophylline (0.3 mg/kg.h-1). The primary outcomes included the levels of serum creatinine (Scr), creatinine clearance rate (Ccr), blood urea nitrogen (BUN), glomerular filtration rate (GFR), and urine output on admission and on days 3, 7 and 14. The secondary outcomes were the sequential organ failure assessment (SOFA) scores, continuous renal replacement therapy (CRRT) time and intensive care unit (ICU) mortality, hospital mortality and 28-day mortality. There were no significant differences in the levels of Scr, Ccr, BUN, or GFR between the two groups, while the urine output was higher in the intervention group on days 3, 7, and 14. Compared with the control group, the SOFA scores, ICU mortality, hospital mortality and 28-day mortality were significantly lower in the intervention group on days 3, 7, and 14, the CRRT time was shorter, and the cumulative fluid balance was lower on days 3 and 7 in the intervention group. CONCLUSIONS: Although low-dose furosemide and aminophylline have fewer protective effects on the renal function in septic shock patients, they could reduce the CRRT time and improve the prognosis.

DNA-templated copper nanocluster: A robust and universal fluorescence switch for bleomycin assay.

Bleomycin (BLM) is widely utilized for cancer treatment due to the outstanding antitumor activity, but BLM with imprecisely controlled dosage may lead to lethal consequences. It is thus a profound task to accurately monitor the BLM levels in clinical settings. Herein, we propose a straightforward, convenient, and sensitive sensing method for BLM assay. Poly-T DNA-templated copper nanoclusters (CuNCs) are fabricated with strong fluorescence emission and uniform size distribution and served as fluorescence indicators for BLM. The high binding affinity of BLM for Cu2+makes it able to inhibit fluorescence signals generated from CuNCs. This is the underlying mechanism rarely explored and can be utilized for effective BLM detection. A detection limit of 0.27 µM (according to 3σ/s rule) is achieved in this work. And the precision, producibility, and practical useability are also confirmed with satisfactory results. Furthermore, the accuracy of the method is verified by high-performance liquid chromatography (HPLC). To sum up, the established strategy in this work exhibits the advantages of convenience, rapidness, low cost, and high precision. The construction of BLM biosensors is important to achieve the best therapeutic effect with minimal toxicity, which opens a new avenue for monitoring antitumor drugs in clinical settings.

miR-150-5p in neutrophil-derived extracellular vesicles associated with sepsis-induced cardiomyopathy in septic patients.

INTRODUCTION: Early diagnosis and potential therapeutic targets of sepsis-induced cardiomyopathy (SIC) remain challenges clinically. Circulating extracellular vesicles from immune cells carrying crucial injurious mediators, including miRNAs in sepsis. However, the impacts of neutrophil-derived extracellular vesicles and their miRNAs in the SIC development are unknown. OBJECTIVES: The present study focused on the in-depth miRNA expression profiles of neutrophil-derived extracellular vesicles and explored the potential molecular biomarkers during the process of SIC. METHODS: Neutrophil-derived extracellular vesicles were isolated from the blood samples in three sepsis patients with or without cardiomyopathy on day 1 and day 3 after ICU admission in comparison with three healthy controls. miRNAs were determined by RNA sequencing. The closely related differentially expressed miRNAs with SIC were further validated through qRT-PCR in the other cohorts of sepsis patients with (30 patients) or without cardiomyopathy (20 patients) and the association between miRNAs and the occurrence or disease severity of septic cardiomyopathy were stratified with logistic regression analysis. RESULTS: Sixty-eight miRNAs from neutrophil-derived extracellular vesicles were changed significantly between healthy controls and without septic cardiomyopathy patients (61 miRNAs upregulated and seven downregulated). Thirty-eight miRNAs were differentially expressed in the septic cardiomyopathy patients. 27 common differentially expressed miRNAs were found in both groups with similar kinetics (23 miRNAs upregulated and four downregulated). The enriched cellular signaling pathway mediated by miRNAs from sepsis to septic cardiomyopathy was the HIF-1 signaling system modulated septic inflammation. Using multivariate logistic regression analysis, miR-150-5p coupled with NT-pro BNP, LVEF, and SOFA score (AUC = 0.941) were found to be the independent predictors of septic cardiomyopathy. CONCLUSION: miRNAs derived from neutrophil-derived extracellular vesicles play an important role in septic disease severity development towards cardiomyopathy. miR-150-5p may be a predictor of sepsis severity development but warrants further study.

Efficacy, Safety and Pharmacokinetics of IL-17 Monoclonal Antibody Injection (AK111) in Patients with Moderate-to-Severe Plaque Psoriasis: A Randomized, Double-Blinded, Placebo-Controlled Phase Ib Multidose Escalation Clinical Study.

OBJECTIVES: To evaluate the safety, tolerability, immunogenicity, and induced expression of skin biomarkers of AK111 injection after multiple administrations in subjects with moderate-to-severe plaque psoriasis. METHODS: This study is a randomized, double-blinded, placebo-parallel-controlled study using a dose escalation mode of multiple doses. A total of 48 subjects were sequentially randomized to receive each AK111 dose regimen (75 mg, 150 mg, 300 mg, 450 mg) or the corresponding placebo. All subjects were treated with the study drug at weeks 0, 1, 4, and 8 and were unblinded at week 12, with the placebo group ending and the AK111 group being followed up to 20 weeks. RESULTS: At week 12, compared with placebo, the percentage of subjects achieving Psoriasis Area and Severity Index 75 (PASI75) and static Physician Global Assessment (sPGA) 0/1 in the AK111 75 mg-450 mg dose groups was significantly increased, and higher PASI90 was achieved in the 150 mg, 300 mg, and 450 mg dose groups than in the 75 mg group. All efficacy indicators were maintained at week 20. The incidence of treatment-emergent anti-drug antibodies (ADAs) was 0% (0/48). Neutralizing antibodies (NAbs) were not detected in any subject. The proportion of subjects who reported any treatment-emergent adverse event (TEAE) was 75.0% in the AK111 group, similar to the 66.7% in the placebo group. The most commonly reported adverse events were hyperglycemia, elevated blood pressure, and hypokalemia. The AK111 pharmacokinetics showed approximate dose proportionality with regard to the maximum observed concentration (Cmax) and area under the curve from 0 to the time of the last quantifiable concentration (AUC0-t) following subcutaneous injection doses of 150-450 mg. CONCLUSIONS: After moderate-to-severe plaque psoriasis subjects received multiple subcutaneous AK111 injections of 150-450 mg, AK111 exposure increased in a roughly dose-proportional relationship. AK111 was safe and tolerable. In subjects with moderate-to-severe plaque psoriasis, AK111 demonstrated encouraging preliminary efficacy, which was sustained for a relatively long time after the last dose administration. CLINICAL TRIAL REGISTRATION: The clinical trial identification number is NCT05504317.