Multi-sequence generative adversarial network: better generation for enhanced magnetic resonance imaging images.

Introduction: MRI is one of the commonly used diagnostic methods in clinical practice, especially in brain diseases. There are many sequences in MRI, but T1CE images can only be obtained by using contrast agents. Many patients (such as cancer patients) must undergo alignment of multiple MRI sequences for diagnosis, especially the contrast-enhanced magnetic resonance sequence. However, some patients such as pregnant women, children, etc. find it difficult to use contrast agents to obtain enhanced sequences, and contrast agents have many adverse reactions, which can pose a significant risk. With the continuous development of deep learning, the emergence of generative adversarial networks makes it possible to extract features from one type of image to generate another type of image. Methods: We propose a generative adversarial network model with multimodal inputs and end-to-end decoding based on the pix2pix model. For the pix2pix model, we used four evaluation metrics: NMSE, RMSE, SSIM, and PNSR to assess the effectiveness of our generated model. Results: Through statistical analysis, we compared our proposed new model with pix2pix and found significant differences between the two. Our model outperformed pix2pix, with higher SSIM and PNSR, lower NMSE and RMSE. We also found that the input of T1W images and T2W images had better effects than other combinations, providing new ideas for subsequent work on generating magnetic resonance enhancement sequence images. By using our model, it is possible to generate magnetic resonance enhanced sequence images based on magnetic resonance non-enhanced sequence images. Discussion: This has significant implications as it can greatly reduce the use of contrast agents to protect populations such as pregnant women and children who are contraindicated for contrast agents. Additionally, contrast agents are relatively expensive, and this generation method may bring about substantial economic benefits.

Overview of indigo biosynthesis by Flavin-containing Monooxygenases: History, industrialization challenges, and strategies.

Indigo is a natural dye extensively used in the global textile industry. However, the conventional synthesis of indigo using toxic compounds like aniline, formaldehyde, and hydrogen cyanide has led to environmental pollution and health risks for workers. This method also faces growing economic, sustainability, and environmental challenges. To address these issues, the concept of bio-indigo or indigo biosynthesis has been proposed as an alternative to aniline-based indigo synthesis. Among various enzymes, Flavin-containing Monooxygenases (FMOs) have shown promise in achieving a high yield of bio-indigo. However, the industrialization of indigo biosynthesis still encounters several challenges. This review focuses on the historical development of indigo biosynthesis mediated by FMOs. It highlights several factors that have hindered industrialization, including the use of unsuitable chassis (Escherichia coli), the toxicity of indole, the high cost of the substrate L-tryptophan, the water-insolubility of the product indigo, the requirement of reducing reagents such as sodium dithionite, and the relatively low yield and high cost compared to chemical synthesis. Additionally, this paper summarizes various strategies to enhance the yield of indigo synthesized by FMOs, including redundant sequence deletion, semi-rational design, cheap precursor research, NADPH regeneration, large-scale fermentation, and enhancement of water solubility of indigo.

Association of the Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) score with immune checkpoint inhibitor efficacy in patients with gastrointestinal and lung cancer.

OBJECTIVE: This study aimed to conduct a comprehensive analysis, evaluating the prognostic significance of the baseline Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) Score in patients undergoing immune checkpoint inhibitor (ICI) therapy. METHODS: A comprehensive search was performed across various databases, including PubMed, the Cochrane Library, EMBASE, and Google Scholar, until October 21, 2023, to compile relevant articles for analysis. The investigation encompassed diverse clinical outcomes, including overall survival (OS) and progression-free survival (PFS). RESULTS: This analysis included a total of 15 articles, comprising 19 studies involving 3335 patients. Among the 19 studies, nine studies focused on NSCLC, and six studies were conducted on HCC. Pooled results revealed that patients with elevated ALI levels experienced prolonged OS (HR: 0.51, 95% CI: 0.37-0.70, p < 0.001) and extended PFS (HR: 0.61, 95% CI: 0.52-0.72, p < 0.001). Furthermore, a GRIm score > 1 was associated with reduced OS (HR: 2.07, 95% CI: 1.47-2.92, p < 0.001) and diminished PFS (HR: 1.78, 95% CI: 1.35-2.34, p < 0.001) in cancer patients receiving ICIs. Subgroup analysis indicated that ALI cutoff values of 18 exhibited enhanced predictive potential. Additionally, for HCC patients, those with HCC-GRIm score > 2 showed a substantially decreased risk of mortality compared to individuals with HCC-GRIm score ≤ 2 (HR: 2.63, 95% CI: 1.89-3.65, p < 0.001). CONCLUSION: The ALI and GRIm score served as dependable prognostic indicators for patients undergoing ICI therapy in the context of cancer treatment.

Diagnostic value of procalcitonin in patients with periprosthetic joint infection: a diagnostic meta-analysis.

Background: The success rate of periprosthetic joint infection (PJI) treatment is still low. Early diagnosis is the key to successful treatment. Therefore, it is necessary to find a biomarker with high sensitivity and specificity. The diagnostic value of serum procalcitonin (PCT) for PJI was systematically evaluated to provide the theoretical basis for clinical diagnosis and treatment in this study. Methods: We searched the Web of Science, Embase, Cochrane Library, and PubMed for studies that evaluated the diagnostic value of serum PCT for PJI (from the inception of each database until September 2020). Two authors independently screened the literature according to the inclusion and exclusion criteria. The quality of each selected literature was evaluated by using the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) tool. RevMan 5.3 software was used for the quality evaluation. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were merged by using Meta-DiSc 1.4 software. The area under the curve (AUC) and Q index were calculated after the summary receiver operating characteristic (SROC) was generated. We also performed subgroup analysis. Results: A total of 621 patients were enrolled in the nine studies. The pooled sensitivity of serum PCT for PJI diagnosis was 0.441 [95% confidence interval (CI), 0.384-0.500], the pooled specificity was 0.852 (95% CI, 0.811-0.888), the pooled PLR was 2.271 (95% CI, 1.808-2.853), the pooled NLR was 0.713 (95% CI, 0.646-0.786), and the pooled DOR was 5.756 (95% CI, 3.673-9.026). The area under SROC (the pooled AUC) was 0.76 (0.72-0.79). Q index was 0.6948. Conclusion: This study showed that PCT detection of PJI had poor diagnostic accuracy. Hence, the serum PCT is not suitable as a serum marker for PJI diagnosis.

Advances in Fluorescent Nanosensors for Detection of Vitamin B12.

Vitamin B12 plays a significant role in maintaining human health. Deficiency or excess intake of vitamin B12 may cause some diseases. Therefore, it is significant to fabricate sensors for sensitive assay of vitamin B12. In the past few years, a variety of nanomaterials have been developed for the fluorescence detection of vitamin B12 in tablets, injection, human serum and food. In the review, the assay mechanisms of fluorescent nanomaterials for sensing vitamin B12 were first briefly discussed. And the progress of various nanomaterials for fluorescence detection of vitamin B12 were systematically summarized. Furthermore, the sensing performance of fluorescent nanosensors was compared with fluorescent probes. Lastly, the challenges and perspectives about the topic were presented.

Effect of brominated flame retardants exposure on liver function and the risk of non-alcoholic fatty liver disease in the US population.

BACKGROUND: The relationship between brominated flame retardants (BFRs) exposure and the human liver was still not well understood. METHODS: A total of 3108 participants (age > 12) from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2005 to 2016 were included as the study population, with nine BFRs exhibiting a detection rate of over 70% serving as the exposure factor. The singular effects and combined effects of BFRs exposure on liver injury, non-alcoholic fatty liver disease (NAFLD), and advanced hepatic fibrosis (AHF) were evaluated separately. Finally, COX regression was employed to explore the hazard ratios associated with individual BFRs. RESULTS: In our analysis of individual exposures, we found significant positive association of PBB153 with alanine aminotransferase (ALT), PBB153 with aspartate aminotransferase (AST), PBDE47, PBDE85, PBDE99, PBDE100, and PBDE154 with alkaline phosphatase (ALP), PBDE28 and PBB153 with gamma-glutamyl transaminase (GGT), PBB153 with the risk of NAFLD and AHF; and significant negative association of PBB153 with ALP, PBDE28, PBDE47, PBDE99, PBDE100, PBDE85, PBDE209, and PBDE154 with albumin (ALB), PBB153 with AST/ALT. The nonlinear analysis results from Restricted Cubic Spline (RCS) further validated these associations (all P<0.05). In the mixed analysis combining Weighted Quantile Sum (WQS) regression and Quantile G-computation (QGC) analysis, BFRs were positively associated with ALT (ß>0, P<0.001), GGT (ß>0, P<0.001), and the risk of NAFLD (OR>1, P=0.007). Conversely, BFRs exhibited significant negative correlations with ALP (ß<0, P<0.001), ALB (ß<0, P<0.001), and AST/ALT (ß<0, P<0.001). Furthermore, the COX regression analysis revealed that PBB153 had the highest hazard ratio among the BFRs. CONCLUSIONS: BFR exposure may increase the risk of liver injury and NAFLD, with no significant association with AHF risk. The impact of BFR exposure on liver health should not be overlooked, especially in individuals residing in impoverished areas.

Nanomaterials for Fluorescent Detection of Hemoglobin.

Hemoglobin plays a vital role in a series of biological activities. Abnormal levels of hemoglobin in blood are associated with many clinical diseases. Therefore, development of simple and accurate methods for sensing hemoglobin is of considerable significance. The blowout advancement in nanotechnology has urged the use of different types of fluorescent nanomaterials for hemoglobin assay. The past decades have witnessed the rapid progress of fluorescent nanosensors for hemoglobin assay. In the review, the sensing principles of fluorescent nanomaterials for sensing hemoglobin were briefly discussed. The advances of fluorescent nanosensors for detection of hemoglobin were further highlighted. And the sensing performance of fluorescent nanosensors versus traditional detection approaches was compared. Finally, the challenges and future directions of fluorescent nanomaterials for detection of hemoglobin are discussed. The review will arouse much more attention to the construction of hemoglobin sensors and facilitate rapid development of fluorescent nanosensors of hemoglobin.

Integrated metabolomics revealed the photothermal therapy of melanoma by Mo2C nanosheets: toward rehabilitated homeostasis in metabolome combined lipidome.

Melanoma, the most aggressive and life-threatening form of skin cancer, lacks innovative therapeutic approaches and deeper bioinformation. In this study, we developed a photothermal therapy (PTT) based on Mo2C nanosheets to eliminate melanoma while utilizing integrated metabolomics to investigate the metabolic shift of metabolome combined lipidome during PTT at the molecular level. Our results demonstrated that 1 mg ml-1 Mo2C nanosheets could efficiently convert laser energy into heat with a strong and stable photothermal effect (74 ± 0.9 °C within 7 cycles). Furthermore, Mo2C-based PTT led to a rapid decrease in melanoma volume (from 3.299 to 0 cm2) on the sixth day, indicating the effective elimination of melanoma. Subsequent integrated metabolomics analysis revealed significant changes in aqueous metabolites (including organic acids, amino acids, fatty acids, and amines) and lipid classes (including phospholipids, lysophospholipids, and sphingolipids), suggesting that melanoma caused substantial fluctuations in both metabolome and lipidome, while Mo2C-based PTT helped improve amino acid metabolism-related biological events (such as tryptophan metabolism) impaired by melanoma. These findings suggest that Mo2C nanosheets hold significant potential as an effective therapeutic agent for skin tumors, such as melanoma. Moreover, through exploring multidimensional bioinformation, integrated metabolomics technology provides novel insights for studying the metabolic effects of tumors, monitoring the correction of metabolic abnormalities by Mo2C nanosheet therapy, and evaluating the therapeutic effect on tumors.

Bone Healing and Clinical Outcome Following Medial Opening-wedge High Tibial Osteotomy Using Wedge-Shaped Cancellous Allograft.

OBJECTIVE: Medial opening-wedge high tibial osteotomy (MOWHTO) is considered to be an effective treatment for symptomatic knee osteoarthritis (KOA) of isolated the medial compartment with varus alignment of the lower extremity. However, the choice of material to fill the void remains controversial. This study aims to evaluate the bone union of the osteotomy gap using a novel wedge-shaped cancellous allograft after MOWHTO and its effect on clinical outcomes. METHODS: All patients who underwent MOWHTO using a novel wedge-shaped cancellous allograft combined with TomoFix locking compression plate (LCP) fixation between January 2016 and July 2020 were enrolled. The radiographic parameters including hip-knee-ankle angle (HKAA), medial proximal tibial angle (MPTA), femorotibial angle (FTA) and posterior tibial slope angle (PTSA) were measured between pre-operative and post-operative radiographs. Knee Society score (KSS) and range of motion (ROM) were assessed preoperatively and at last follow-up. Patients included in this study were divided into two groups according to the correction angle: small correction group (< 10°; SC group) and large correction group (≥ 10°; LC group). The modified Radiographic Union score for tibial fractures (mRUST) was used to assess the difference in bone healing between the two groups at 1, 3, 6, and 12 months postoperatively and at the final follow-up. A paired student's t test was conducted for comparison of differences of the relevant data pre-operatively and post-operatively. RESULTS: A total of 82 patients (88 knees) were included in this study. The HKAA, MPTA, FTA and PTSA increased from -6.4° ± 3.0°, 85.1° ± 2.6°, 180.1° ± 3.2° and 7.7° ± 4.4° preoperatively to 1.2° ± 4.3° (p < 0.001), 94.4° ± 3.3° (p < 0.001), 171.0° ± 2.8° and 11.8° ± 5.8° (p < 0.001) immediately postoperatively, respectively. However, no significant statistic difference was found in above-mentioned parameters at last follow-up compared to immediate postoperative data (p > 0.05). All patients in this study achieved good bone healing at the final follow-up and no significant differences in mRUST scores were seen between the SC group and LC group. The KSS-Knee score and KSS-Function score improved significantly from 55.4 ± 3.7 and 63.3 ± 4.6 preoperatively to 86.4 ± 2.8 (p < 0.001) and 89.6 ± 2.9 (p < 0.001) at last follow-up, respectively. Nevertheless, there was no significant difference in ROM between pre-operation and last follow-up (p > 0.05). CONCLUSION: For MOWHTO, the wedge-shaped cancellous allograft was a reliable choice for providing good bone healing and clinical outcomes.

The accuracy of multiple regression models for predicting the individual risk of recurrent lateral patellar dislocation.

BACKGROUND: Recurrent lateral patellar dislocation (RLPD) poses a significant threat to patients' quality of life due to knee pain, patellofemoral cartilage damage, and potential traumatic arthritis. Predictive scoring systems have been developed to assess the risk of RLPD; however, their relative accuracy remains uncertain. PURPOSE: To investigate the accuracy of the multiple regression models to predict the individual risk of recurrent LPD. METHODS: The Patellar Instability probability calculator (PIP), Recurrent Instability of the Patella Score (RIP), and Patellar Instability Severity Score (PIS) scoring rules were measured in 171 patients with a history of patellar dislocation and 171 healthy individuals. Three prediction models were calculated based on the data to predict the risk of recurrent lateral patellar dislocation. The inter-observer and intra-observer reliability of each measurement parameter was evaluated. The predictive capacity of the three-prediction model was investigated using the receiver operating characteristic curve. RESULTS: In the case group of 171 patients, PIS accurately predicted recurrent lateral Patella dislocation in 143 patients. RIP was 96, and PIP was 83. The positive predictive values were 92.9%, 64%, and 68% respectively. In the control group of 171 patients, the PIS was validated in 160 patients who would not experience dislocations. RIP was 117, and PIP was 50. The negative predictive values were 85.1%, 60.9%, and 36.2%, respectively. The area under the curve score for the PIS was 0.866, and the RIP was 0.673. the PIP was 0.678. CONCLUSION: RIP and PIP did not work to predict LPD. PIS can accurately predict recurrent lateral patellar dislocation. It can aid doctors in making treatment decisions. LEVEL OF EVIDENCE: Level III, retrospective comparative study.

Double-edged functions of hemopexin in hematological related diseases: from basic mechanisms to clinical application.

It is now understood that hemolysis and the subsequent release of heme into circulation play a critical role in driving the progression of various diseases. Hemopexin (HPX), a heme-binding protein with the highest affinity for heme in plasma, serves as an effective antagonist against heme toxicity resulting from severe acute or chronic hemolysis. In the present study, changes in HPX concentration were characterized at different stages of hemolytic diseases, underscoring its potential as a biomarker for assessing disease progression and prognosis. In many heme overload-driven conditions, such as sickle cell disease, transfusion-induced hemolysis, and sepsis, endogenous HPX levels are often insufficient to provide protection. Consequently, there is growing interest in developing HPX therapeutics to mitigate toxic heme exposure. Strategies include HPX supplementation when endogenous levels are depleted and enhancing HPX's functionality through modifications, offering a potent defense against heme toxicity. It is worth noting that HPX may also exert deleterious effects under certain circumstances. This review aims to provide a comprehensive overview of HPX's roles in the progression and prognosis of hematological diseases. It highlights HPX-based clinical therapies for different hematological disorders, discusses advancements in HPX production and modification technologies, and offers a theoretical basis for the clinical application of HPX.

An ECG Signal Acquisition and Analysis System Based on Machine Learning with Model Fusion.

Recently, cardiovascular disease has become the leading cause of death worldwide. Abnormal heart rate signals are an important indicator of cardiovascular disease. At present, the ECG signal acquisition instruments on the market are not portable and manual analysis is applied in data processing, which cannot address the above problems. To solve these problems, this study proposes an ECG acquisition and analysis system based on machine learning. The ECG analysis system responsible for ECG signal classification includes two parts: data preprocessing and machine learning models. Multiple types of models were built for overall classification, and model fusion was conducted. Firstly, traditional models such as logistic regression, support vector machines, and XGBoost were employed, along with feature engineering that primarily included morphological features and wavelet coefficient features. Subsequently, deep learning models, including convolutional neural networks and long short-term memory networks, were introduced and utilized for model fusion classification. The system's classification accuracy for ECG signals reached 99.13%. Future work will focus on optimizing the model and developing a more portable instrument that can be utilized in the field.

Proteomic Study on Multi-Organ Metastases of Human Ovarian Clear Cell Carcinoma Cell Line in a Xenograft Mouse Model Based on a Novel Sequence-Specific Analysis Strategy.

BACKGROUND: To investigate the gene regulation of tumor cells in the process of different organ metastasis on a xenograft mouse model and screen the genes involved in the organ-target metastasis of tumor cells. METHODS: A multi-organ metastasis model was constructed with a human ovarian clear cell carcinoma cell line (ES-2) based on a severe immunodeficiency mouse strain (NCG). Differentially expressed tumor proteins among multi-organ metastases were successfully characterized by microliter liquid chromatography-high-resolution mass spectrometry, sequence-specific data analysis and multivariate statistical data analysis. Liver metastases were selected as typical for subsequent bioinformatic analysis. Selected liver metastasis-specific genes in ES-2 cells were validated by sequence-specific quantitation including high resolution-multiple reaction monitoring quantification at protein level and quantitative real-time polymerase chain reaction at mRNA level. RESULTS: From the mass spectrometry data, a total of 4503 human proteins were identified using the sequence-specific data analysis strategy. Of them, 158 proteins were selected as specifically regulated genes in liver metastases for subsequent bioinformatics studies. Based on Ingenuity Pathway Analysis (IPA) pathway analysis and sequence-specific quantitation, Ferritin light chain (FTL), lactate dehydrogenase A (LDHA) and long-chain-fatty-acid-CoA ligase 1 (ACSL1) were finally validated as specifically upregulated proteins in liver metastases. CONCLUSIONS: Our work provides a new approach to analyze gene regulation in tumor metastasis in xenograft mouse model. In presence of a large number of mouse protein interference, we validated the up-regulation of human ACSL1, FTL and LDHA in ES-2 liver metastases, which reflects the adaptive regulation of tumor cells to the liver microenvironment through metabolic reprogramming.

Carbon quantum dots for fluorescent detection of nitrite: A review.

NO2- is commonly found in foods and the environment, and excessive intake of NO2- poses serious hazards to human health. Thus, rapid and accurate assay of NO2- is of considerable significance. Traditional instrumental approaches for detection of NO2- faced with limitations of expensive instruments and complicated operations. Current gold standards for sensing NO2- are Griess assay and 2,3-diaminonaphthalene assay, which suffer from slow detection kinetics and bad water solubility. The newly emerged carbon quantum dots (CQDs) exhibit integrated merits including easy fabrication, low-cost, high quantum yield, excellent photostability, tunable emission behavior, good water solubility and low toxicity, which make CQDs be widely applied to fluorescent assay of NO2-. In this review, synthetic strategies of CQDs are briefly presented. Advances of CQDs for fluorescent detection of NO2- are systematically highlighted. Lastly, the challenges and perspectives in the field are discussed.

Vitamin D and neurodegenerative diseases.

Neurodegenerative diseases, featured by progressive loss of structure or function of neurons, are considered incurable at present. Movement disorders like tremor and postural instability, cognitive or behavioral disorders such as memory impairment are the most common symptoms of them and the growing patient population of neurodegenerative diseases poses a serious threat to public health and a burden on economic development. Hence, it is vital to prevent the occurrence of the diseases and delay their progress. Vitamin D can be transformed into a hormone in vivo with both genomic and non-genomic actions, exerting diverse physiological effects. Cumulative evidence indicates that vitamin D can ameliorate neurodegeneration by regulating pertinent molecules and signaling pathways including maintaining Ca2+ homeostasis, reducing oxidative stress, inhibiting inflammation, suppressing the formation and aggregation of the pathogenic protein, etc. This review updates discoveries of molecular mechanisms underlying biological functions of vitamin D in neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and vascular dementia. Clinical trials investigating the influence of vitamin D supplementation in patients with neurodegenerative diseases are also summarized. The synthesized information will probably provoke an enhanced understanding of the neuroprotective roles of vitamin D in the nervous system and provide therapeutic options for patients with neurodegenerative diseases in the future.

The Prognostic Value of the GNRI in Patients with Stomach Cancer Undergoing Surgery.

Malnutrition often induces an adverse prognosis in cancer surgery patients. The elderly nutrition risk index (GNRI) is an example of the objective indicators of nutrition-related risks. We performed a meta-analysis to thoroughly examine the evidence for the GNRI in predicting the outcomes of patients undergoing stomach cancer surgery. Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by 24 October 2022. The clinical outcomes were overall survival (OS), cancer-specific survival (CSS), and post-operative complications. A total of 11 articles with 5593 patients were included in this meta-analysis. The combined forest plot showed that for every unit increase in the preoperative GNRI score in patients with stomach cancer, their postoperative mortality was reduced by 5.6% (HR: 0.944; 95% CI: 0.933−0.956, p < 0.001). The pooled results also demonstrated that a low GNRI was correlated with poor OS (HR: 2.052; 95% CI: 1.726−2.440, p < 0.001) and CSS (HR: 1.684; 95% CI: 1.249−2.270, p = 0.001) in patients who underwent stomach cancer surgery. Postoperative complications were more likely to occur in patients with a low GNRI, as opposed to those with a high GNRI (OR: 1.768; 95% CI: 1.445−2.163, p < 0.001). There was no evidence of significant heterogeneity, and the sensitivity analysis supported the stability and dependability of the above results. the GNRI is a valuable predictor of long-term outcomes and complications in stomach cancer patients undergoing surgery.

CD8+ T cell-intrinsic IL-6 signaling promotes resistance to anti-PD-L1 immunotherapy.

Although immune checkpoint inhibitors (ICIs) are established as effective cancer therapies, overcoming therapeutic resistance remains a critical challenge. Here we identify interleukin 6 (IL-6) as a correlate of poor response to atezolizumab (anti-PD-L1) in large clinical trials of advanced kidney, breast, and bladder cancers. In pre-clinical models, combined blockade of PD-L1 and the IL-6 receptor (IL6R) causes synergistic regression of large established tumors and substantially improves anti-tumor CD8+ cytotoxic T lymphocyte (CTL) responses compared with anti-PD-L1 alone. Circulating CTLs from cancer patients with high plasma IL-6 display a repressed functional profile based on single-cell RNA sequencing, and IL-6-STAT3 signaling inhibits classical cytotoxic differentiation of CTLs in vitro. In tumor-bearing mice, CTL-specific IL6R deficiency is sufficient to improve anti-PD-L1 activity. Thus, based on both clinical and experimental evidence, agents targeting IL-6 signaling are plausible partners for combination with ICIs in cancer patients.

Facile one-pot synthesis of fluorescent aminoclay and the applications for fluorescence sensing Cr2 O7 2.

Here, we developed a facile one-pot strategy for the fabrication of fluorescent aminoclay (F-AC) through in situ solvothermal treatment of 3-aminopropyltrimethoxysilane, MgCl2 , and sodium ascorbate at 180°C for 6 h. The obtained F-AC exhibited blue emission, good water solubility, and satisfactory photostability. It was observed that Cr2 O7 2- could selectively quench the fluorescence of F-AC through the inner filter effect and static quenching process. As a result, a novel fluorescent F-AC-based nanosensor was constructed with good linearity in the range 0.1-75 µM. The nanosensor was successfully applied in real water samples with satisfactory results. This work not only provides a novel nanosensor for Cr2 O7 2- , but also highlights the F-AC's promising applications in wider fields due to the versatility and simplicity of the preparation strategy.

Predictors and complications of blood transfusion in rheumatoid arthritis patients undergoing total joint arthroplasty.

PURPOSE: Our research investigated predictors of postoperative blood transfusion rate following total joint arthroplasty (TJA) in patients with rheumatoid arthritis (RA) and evaluated the incidence of complications in the transfusion group and non-transfusion group. METHODS: The authors retrospectively analyzed risk factors among 320 RA patients who underwent elective total hip arthroplasty (THA) or total knee arthroplasty (TKA) from January 2010 to December 2018. Demographic characteristics, laboratory results, medication history, and surgical protocol were gathered from electronic medical records. Univariable and multivariable logistic regression analyses were conducted to measure the impact of relevant variables on the need for transfusions. In addition, we compared the incidence of complications associated with transfusion. RESULTS: The cohort comprised 320 RA patients, aged 57.4 ± 12.0 years, of whom 137 required postoperative blood transfusions and 183 did not. BMI, type of surgery, duration of surgery, disease activity score 28 (DAS28-CRP), tranexamic acid (TXA) administration, and preoperative hemoglobin (Hb) were all risk factors for transfusion after adjusting for the planned procedure. CONCLUSION: Previously published predictors, such as BMI, low preoperative hemoglobin, duration of surgery, procedure type (THA), were also identified in our analysis. Moreover, TXA administration and the DAS28-CRP showed the potential to influence risk. The incidence of postoperative complications was increased in patients who received blood transfusions compared to non-transfusion group. Our findings could help to identify RA patient population requiring blood transfusions, to ensure the necessary steps are adopted to limit blood loss and improve blood management strategies. Key Points • The risk factors for blood transfusion in rheumatoid arthritis patients undergoing total joint arthroplasty were BMI, the type of surgery, duration of surgery, TXA administration, DAS28-CRP, and preoperative hemoglobin. • The incidence of postoperative complications was increased in patients who received blood transfusions compared to non-transfusion group.