Microbial cancer immunotherapy reprograms hematopoietic stem cells to enhance anti-tumor immunity.

Mycobacterium bovis BCG is the vaccine against tuberculosis and an immunotherapy for bladder cancer. When administered intravenously, BCG reprograms bone marrow hematopoietic stem and progenitor cells (HSPCs), leading to heterologous protection against infections. Whether HSPC-reprogramming contributes to the anti-tumor effects of BCG administered into the bladder is unknown. We demonstrate that BCG administered in the bladder in both mice and humans reprograms HSPCs to amplify myelopoiesis and functionally enhance myeloid cell antigen presentation pathways. Reconstitution of naive mice with HSPCs from bladder BCG-treated mice enhances anti-tumor immunity and tumor control, increases intratumoral dendritic cell infiltration, and synergizes with checkpoint blockade. We conclude that bladder BCG acts systemically, reprogramming HSPC-encoded innate immunity, highlighting the broad potential of modulating HSPC phenotypes to improve tumor immunity. One Sentence Summary: BCG administered in the bladder reprograms bone marrow HSPCs and contributes to tumor control via enhanced myeloid cells.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Inhibition of HDAC6 with CAY10603 alleviates acute and chronic kidney injury by suppressing the ATF6 branch of UPR.

BACKGROUND: Histone deacetylase 6 (HDAC6) inhibitor CAY10603 has been identified as a potential therapeutic agent for the treatment of diabetic kidney disease (DKD). The objective of this study was to investigate the therapeutic effects of CAY10603 in mice with acute kidney injury (AKI) and chronic kidney diseases (CKD). METHODS: Renal immunohistology was performed to assess the expression levels of HDAC6 in both human and mouse kidney samples. C57BL/6J mice were intraperitoneal injected with lipopolysaccharide (LPS) to induce AKI; CD-1 mice were fed with adenine diet to induce adenine-nephropathy as CKD model. Serum creatinine, blood urea nitrogen and uric acid were measured to reflect renal function; renal histology was applied to assess kidney damage. Western blot and immunohistology were used to analyze the unfolded protein response (UPR) level. RESULTS: HDAC6 was significantly upregulated in renal tubular epithelial cells (RTECs) of both AKI and CKD patients as well as mice. In the murine models of AKI induced by LPS and adenine-induced nephropathy, CAY10603 exhibited notable protective effects, including improvement in biochemical indices and pathological changes. In vivo and in vitro studies revealed that CAY10603 effectively suppressed the activation of activating transcription factor 6 (ATF6) branch of UPR triggered by thapsigargin (Tg), a commonly employed endoplasmic reticulum (ER) stressor. Consistent with these findings, CAY10603 also displayed substantial inhibition of ATF6 activation in RTECs from both murine models of LPS-induced AKI and adenine-induced nephropathy. CONCLUSIONS: Collectively, these results suggest that CAY10603 holds promise as a potential therapeutic agent for both acute and chronic kidney injury.

The Index sAGP is Valuable for Distinguishing Atypical Hepatocellular Carcinoma from Atypical Benign Focal Hepatic Lesions.

Purpose: The differential diagnosis of atypical hepatocellular carcinoma (aHCC) and atypical benign focal hepatic lesions (aBFHL) usually depends on pathology. This study aimed to develop non-invasive approaches based on conventional blood indicators for the differential diagnosis of aHCC and aBFHL. Patients and Methods: Hospitalized patients with pathologically confirmed focal hepatic lesions and their clinical data were retrospectively collected, in which patients with HCC with serum alpha-fetoprotein (AFP) levels of ≤200 ng/mL and atypical imaging features were designated as the aHCC group (n = 224), and patients with benign focal hepatic lesions without typical imaging features were designated as the aBFHL group (n = 178). The performance of indexes (both previously reported and newly constructed) derived from conventional blood indicators by four mathematical operations in distinguishing aHCC and aBFHL was evaluated using the receiver operating characteristic (ROC) curve and diagnostic validity metrics. Results: Among ten previously reported derived indexes related to HCC, the index GPR, the ratio of γ-glutamyltransferase (GGT) to platelet (PLT), showed the best performance in distinguishing aHCC from aBFHL with the area under ROC curve (AUROC) of 0.853 (95% CI 0.814-0.892), but the other indexes were of little value (AUROCs from 0.531 to 0.700). A new derived index, sAGP [(standardized AFP + standardized GGT)/standardized PLT], was developed and exhibited AUROCs of 0.905, 0.894, 0.891, 0.925, and 0.862 in differentiating overall, BCLC stage 0/A, TNM stage I, small, and AFP-negative aHCC from aBFHL, respectively. Conclusion: The sAGP index is an efficient, simple, and practical metric for the non-invasive differentiation of aHCC from aBFHL.

Evolution and Trends of Aptamers in Cancer Research: A Bibliometric Analysis of the Literature over the Last Decade.

OBJECTIVE: Aptamers are increasingly applied in cancer research. Here, we have performed the first bibliometric analysis to demonstrate the evolution of aptamers in cancer research over the past decade and to reveal future trends. METHOD: Original articles and reviews on aptamers in cancer research published from 2013 to 2022 were retrieved from the Web of Science Core Collection database. VOSviewer, CiteSpace, and R software were used for bibliometric analysis of the literature and visualization of the results. RESULTS: A total of 1627 eligible publications were analyzed. Annual and cumulative publications have been found to be steadily increased. China was the most productive country (884 publications) and Hunan University was the most productive institution (97 publications). The United States had the highest level of international collaboration (betweenness centrality = 0.55). Wei-Hong Tan was the most productive author (68 publications) and Craig Tuerk was the most cited author (387 citations). Analytical Chemistry and Biosensors and Bioelectronics were the most influential journals in this field. Three major themes were identified: aptamer selection techniques, aptamer-targeted drug delivery, and aptasensors for cancer detection. The research hotspots have shifted from aptamer selection, targeted drug delivery, molecular imaging, and biomarker detection to electrochemical aptasensors and therapeutic applications. The future may focus on high specificity and affinity in aptamer selection, aptasensor fabrication, aptamer- targeted drug delivery, and therapeutic aptamer development. CONCLUSION: The field of aptamers in cancer research has been steadily developing over the past decade, and future research may focus on aptamer application in cancer detection and therapy and the improvement of aptamer selection.

Evaluation of Genetic Parameters and Comparison of Stress Tolerance Traits in Different Strains of Litopenaeus vannamei.

Litopenaeus vannamei stands out globally in aquaculture for its fast growth, broad salt tolerance, disease resistance, and high protein levels. Selective breeding requires the precise estimation of the variance components and genetic parameters for important traits. This study formed lineages from 20 full sibling families of L. vannamei, with progenitors from Thailand and the USA. We then assessed the genetic resilience traits of juvenile shrimp from these families to high ammonia-N, high pH, and low salinity by performing a 96 h acute toxicity test. Mortality rates for the families under 96 h exposure to high ammonia-N, high pH, and low salinity were 19.52-92.22%, 23.33-92.22%, and 19.33-80.00%, respectively, showing significant variance in stress tolerance among families (p < 0.05). Survival heritability estimates, using threshold male and female models, were 0.44 ± 0.12 in high ammonia-N, 0.41 ± 0.12 in high pH, and 0.27 ± 0.08 in low salinity, respectively. Genetic correlations between growth and stress resistance traits varied from 0.0137 ± 0.2406 to 0.8327 ± 0.0781, and phenotypic correlations ranged from 0.0019 ± 0.0590 to 0.6959 ± 0.0107, indicating a low-to-high positive correlation significant at (p < 0.05). It was found that the survival rate of families No. 2 and No. 9 was higher under high ammonia-N and high pH stresses, while the survival rate of family No. 10 was higher under low salinity stress after comparing two selection criteria, the breeding values and phenotypic values. Thus, these three families are identified as potential breeding program candidates. Through the creation of a genetic parameter estimation model, the genetic variances across mating combinations for stress resistance traits were obtained and families with heightened stress resistance were identified, laying the groundwork for enhanced genetic selection of L. vannamei.

Enhanced High-Fructose Corn Syrup Production: Immobilizing Serratia marcescens Glucose Isomerase on MOF (Co)-525 Reduces Co2+ Dependency in Glucose Isomerization to Fructose.

The escalating demand for processed foods has led to the widespread industrial use of glucose isomerase (GI) for high-fructose corn syrup (HFCS) production. This reliance on GIs necessitates continual Co2+ supplementation to sustain high catalytic activity across multiple reaction cycles. In this study, Serratia marcescens GI (SmGI) was immobilized onto surfaces of the metal-organic framework (MOF) material MOF (Co)-525 to generate MOF (Co)-525-GI for use in catalyzing glucose isomerization to generate fructose. Examination of MOF (Co)-525-GI structural features using scanning electron microscopy-energy dispersive spectroscopy, Fourier-transform infrared spectroscopy, and ultraviolet spectroscopy revealed no structural changes after SmGI immobilization and the addition of Co2+. Notably, MOF (Co)-525-GI exhibited optimal catalytic activity at pH 7.5 and 70 °C, with a maximum reaction rate (Vmax) of 37.24 ± 1.91 µM/min and Km value of 46.25 ± 3.03 mM observed. Remarkably, immobilized SmGI exhibited sustained high catalytic activity over multiple cycles without continuous Co2+ infusion, retaining its molecular structure and 96.38% of its initial activity after six reaction cycles. These results underscore the potential of MOF (Co)-525-GI to serve as a safer and more efficient immobilized enzyme technology compared to traditional GI-based food-processing technologies.

Unveiling breast cancer risk profiles: a survival clustering analysis empowered by an online web application.

Aim: To develop a shiny app for doctors to investigate breast cancer treatments through a new approach by incorporating unsupervised clustering and survival information. Materials & methods: Analysis is based on the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which contains 1726 subjects and 22 variables. Cox regression was used to identify survival risk factors for K-means clustering. Logrank tests and C-statistics were compared across different cluster numbers and Kaplan-Meier plots were presented. Results & conclusion: Our study fills an existing void by introducing a unique combination of unsupervised learning techniques and survival information on the clinician side, demonstrating the potential of survival clustering as a valuable tool in uncovering hidden structures based on distinct risk profiles.

Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma.

OBJECTIVE: This study aims to compare the feasibility and effectiveness of automatic deep learning network and radiomics models in differentiating low tumor stroma ratio (TSR) from high TSR in pancreatic ductal adenocarcinoma (PDAC). METHODS: A retrospective analysis was conducted on a total of 207 PDAC patients from three centers (training cohort: n = 160; test cohort: n = 47). TSR was assessed on hematoxylin and eosin-stained specimens by experienced pathologists and divided as low TSR and high TSR. Deep learning and radiomics models were developed including ShuffulNetV2, Xception, MobileNetV3, ResNet18, support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and logistic regression (LR). Additionally, the clinical models were constructed through univariate and multivariate logistic regression. Kaplan-Meier survival analysis and log-rank tests were conducted to compare the overall survival time between different TSR groups. RESULTS: To differentiate low TSR from high TSR, the deep learning models based on ShuffulNetV2, Xception, MobileNetV3, and ResNet18 achieved AUCs of 0.846, 0.924, 0.930, and 0.941, respectively, outperforming the radiomics models based on SVM, KNN, RF, and LR with AUCs of 0.739, 0.717, 0.763, and 0.756, respectively. Resnet 18 achieved the best predictive performance. The clinical model based on T stage alone performed worse than deep learning models and radiomics models. The survival analysis based on 142 of the 207 patients demonstrated that patients with low TSR had longer overall survival. CONCLUSIONS: Deep learning models demonstrate feasibility and superiority over radiomics in differentiating TSR in PDAC. The tumor stroma ratio in the PDAC microenvironment plays a significant role in determining prognosis. CRITICAL RELEVANCE STATEMENT: The objective was to compare the feasibility and effectiveness of automatic deep learning networks and radiomics models in identifying the tumor-stroma ratio in pancreatic ductal adenocarcinoma. Our findings demonstrate deep learning models exhibited superior performance compared to traditional radiomics models. KEY POINTS: • Deep learning demonstrates better performance than radiomics in differentiating tumor-stroma ratio in pancreatic ductal adenocarcinoma. • The tumor-stroma ratio in the pancreatic ductal adenocarcinoma microenvironment plays a protective role in prognosis. • Preoperative prediction of tumor-stroma ratio contributes to clinical decision-making and guiding precise medicine.

[Clinical observation of virtual reality technology combined with isokinetic strength training for patients after anterior cruciate ligament reconstruction].

OBJECTIVE: To explore application value and effectiveness of virtual reality technology combined with isokinetic muscle strength training in the rehabilitation of patients after anterior cruciate ligament (ACL) reconstruction surgery. METHODS: Forty patients who underwent ACL reconstruction surgery from December 2021 to January 2023 were selected and divided into control group and observation group according to treatment methods, 20 patients in each group. Control group was received routine rehabilitation training combined with isokinetic muscle strength training, including 15 males and 5 females, aged from 17 to 44 years old, with an average of (29.10±8.60) years old. Observation group was performed virtual reality technology combined with isokinetic muscle strength training, including 16 males and 4 females, aged from 17 to 45 years old with an average of (30.95±9.11) years old. Lysholm knee joint score, knee extension peak torque, and knee flexion peak torque between two groups at 12 (before training) and 16 weeks (after training) after surgery were compared. RESULTS: All patients were followed up for 1 to 6 months with an average of (3.30±1.42) months. There were no statistically significant difference in Lysholm knee joint score, peak knee extension peak torque, and peak knee flexion peak torque between two groups (P>0.05) before training. After training, Lysholm knee joint score, knee extension peak torque, and knee flexion peak torque of both groups were improved compared to before training (P<0.05);there were significant difference in Lysholm knee joint score, knee extension peak torque, and knee flexion peak torque between two groups(P<0.05). CONCLUSION: The application of virtual reality technology combined with isokinetic muscle strength training could promote recovery of knee joint function and enhance muscle strength in patients after ACL reconstruction surgery in further.

Effect of Fly Maggot Protein as Dietary on Growth and Intestinal Microbial Community of Pacific White Shrimp Litopenaeus vannamei.

As the intensive development of aquaculture persists, the demand for fishmeal continues to grow; however, since fishery resources are limited, the price of fishmeal remains high. Therefore, there is an urgent need to develop new sources of protein. They are rich in proteins, fatty acids, amino acids, chitin, vitamins, minerals, and antibacterial substances. Maggot meal-based diet is an ideal source of high-quality animal protein and a new type of protein-based immune enhancer with good application prospects in animal husbandry and aquaculture. In the present study, we investigated the effects of three different diets containing maggot protein on the growth and intestinal microflora of Litopenaeus vannamei. The shrimp were fed either a control feed (no fly maggot protein added), FM feed (compound feed with 30% fresh fly maggot protein added), FF feed (fermented fly maggot protein), or HT feed (high-temperature pelleted fly maggot protein) for eight weeks. The results showed that fresh fly maggot protein in the feed was detrimental to shrimp growth, whereas fermented and high-temperature-pelleted fly maggot protein improved shrimp growth and survival. The effects of different fly maggot protein treatments on the intestinal microbiota of L. vannamei also varied. Fermented fly maggot protein feed and high-temperature-pelleted fly maggot protein feed increased the relative abundance of Ruegeria and Pseudomonas, which increased the abundance of beneficial bacteria and thus inhibited the growth of harmful bacteria. In contrast, fresh fly maggot proteins alter the intestinal microbiome, disrupting symbiotic relationships between bacteria, and causing invasion by Vibrio and antibiotic-resistant bacteria. These results suggest that fresh fly maggot proteins affect the composition of intestinal microorganisms, which is detrimental to the intestinal tract of L. vannamei, whereas fermented fly maggot protein feed affected the growth of L. vannamei positively by improving the composition of intestinal microorganisms.

Dual-Stimulus-Driven Dynamically Controllable [3]Rotaxane with Tunable Organic Room-Temperature Phosphorescence.

A dual-stimulus-driven stiff-stilbene-based dynamic [3]rotaxane has been facilely developed using the threading-stoppering strategy and exhibits reversible shuttling motions and bidirectional rotations upon encountering acid-base and distinct light stimulations, respectively. Herein, the two dibenzo-24-crown-8 macrocycles can undergo reversible switching motion between two different stations along the axle suffered from acid-base stimulation, and simultaneously, the two rotaxanes can also perform cis-trans rotations upon irradiation with distinct light. In other words, the constructed rotaxanes can conduct two modes of regular motions without interference. Interestingly, reciprocating switching motion of the rings along the axle enabled the rotaxanes to exhibit controllable and reversible photoisomerization speed, conversion yield, and quantum yield. Crucially, these rotaxanes also manifest adjustable solid-state organic room-temperature phosphorescence (RTP) and photoluminescence stimulated by dual factors (acid-base and diverse light), which are further applied in information encryption and anticounterfeiting. The presented study provides an instructive way for precisely boosting photoisomerization performances and the fabrication of dual-stimuli-induced molecular machines with functions of two-mode mechanical motions and controllable pure organic RTP switches.

Cantilever beam bending as a potential method to determine the elasticity of cooked Udon noodles.

Elasticity is a critical measure of the eating quality of Udon noodles. To characterize the elasticity of Udon noodles, an instrumental method based on the cantilever beam bending test was established. Firstly, the optimum test parameters were determined. Then, texture profile analysis, compression, tension, and cantilever beam bending methods were used to measure the elasticity of 25 commercial Udon noodles with different shapes and sizes, and the correlations between elasticity obtained by the above instrumental methods and sensory evaluation were analyzed. Finally, how the shape and size of Udon noodles influenced their elasticity was discussed in detail. Within the deflection of 2.0 mm, the force increased approximately linearly with increasing deflection, and moderate loading speed (0.5-1.0 mm/s) should be used in the cantilever beam bending experiments to improve the accuracy of results. The bending stiffness obtained by the cantilever beam bending method exhibited a higher coefficient of variation and stronger correlation with the elasticity of sensory evaluation than other instrumental methods. Furthermore, the Udon noodle sample with a higher size, especially the thickness, had higher elasticity, and the Udon noodle sample with a rectangular cross-section showed higher elasticity than that with a circular cross-section. In conclusion, the bending stiffness determined by the cantilever beam bending method could be used to characterize the elasticity of cooked Udon noodles.

Bibliometric analysis of aptamer-conjugated nanoparticles for diagnosis in the last two decades.

Objective.Aptamer-conjugated nanoparticles for diagnosis have recently gained increasing attention. Here, we performed a bibliometric analysis to provide an overview of this field over the past two decades.Methods. The terms 'aptamer, nanoparticles and diagnosis' were used to search for relevant original articles published in English from 2003 to 2022 in the Web of Science database. VOSviewer and CiteSpace software were employed to analyze the development process, knowledge structure, research hotspots, and potential trends in the field of aptamer-conjugated nanoparticles for diagnosis.Results. A total of 1076 original articles were retrieved, with a rapid increase in the annual output and citation. The journal 'Biosensors and Bioelectronics' has contributed the most in this field, and the most influential researcher, institution and country were Weihong Tan, the Chinese Academy of Sciences, China, respectively. Gold nanoparticles and quantum dots were the most used, but in the past three years, research hotspots focused on carbon dots and graphene quantum dots. Diagnostic directions primarily focused on cancer. The most used strategy was label-free electrochemical detection, but in the past two years, colorimetric analysis and fluorescence imaging emerged as hot topics.Conclusion.The bibliometric analysis reveals a rapid increase in the research on aptamer-conjugated nanoparticles for diagnosis, major contributors at the levels of journals, authors, institutions, and countries, and research preferences in diagnostic objects, nanoparticle types, and detection methods, as well as the evolution of research hotspots and future trends.

Evaluation of the significance of complement-related genes mutations in atypical postinfectious glomerulonephritis: a pilot study.

BACKGROUND: Postinfectious glomerulonephritis with C3-dominant glomerular deposition (C3-PIGN) involves C3-dominant glomerular deposition without immunoglobulin. Atypical C3-PIGN involves persistent hypocomplementemia. We investigated the clinical features and explored complement-related gene mutations in atypical PIGN patients. METHODS: We enrolled atypical C3-PIGN patients and collected data regarding the clinical presentation and pathological characteristics and follow-up data. We measured the levels of complement associated antibodies and performed whole-exome sequencing (WES) to detect mutations in complement-related genes. RESULTS: The analysis included six atypical C3-PIGN patients. All patients were antistreptolysin-O (ASO) positive. All patients had varying degrees of hematuria, and four patients had proteinuria. None of the patients were positive for complement-related antibodies. All patients possessed mutations of genes related to the complement pathway, including alternative complement pathway genes-CFI, CFH, CFHR3, CFHR5; the lectin pathway gene-MASP2; and the common complement pathway gene-C8A. The rare variant of CFHR3 has been reported in C3 glomerulonephritis. During 56-73 months of follow-up, the levels of urine markers in three patients recovered within 6 months, and the remaining patients had abnormal urine test results over 12 months. Patients who received glucocorticoid therapy recovered faster. CONCLUSIONS: Our study suggested that complement-related gene mutations may be an important cause of persistent hypocomplementemia in atypical C3-PIGN patients. In addition to variations in alternate pathway-related genes, we also found variations in lectin pathway-related genes, especially MASP2 genes. Although the overall prognosis was good, atypical C3-PIGN patients exhibited a longer period for recovery. Our results suggested that atypical C3-PIGN patients should receive more medical attention and need testing for mutations in complement-related genes.

FeIII Chelated with Humic Acid with Easy Synthesis Conditions and Good Performance as Anode Materials for Lithium-Ion Batteries.

In this work, we prepared a green, cheap material by chelating humic acid with ferric ions (HA-Fe) and used it as an anode material in LIBs for the first time. From the SEM, TEM, XPS, XRD, and nitrogen adsorption-desorption experimental results, it was found that the ferric ion can chelate with humic acid successfully under mild conditions and can increase the surface area of materials. Taking advantage of the chelation between the ferric ions and HA, the capacity of HA-Fe is 586 mAh·g-1 at 0.1 A·g-1 after 1000 cycles. Moreover, benefitting from the chelation effect, the activation degree of HA-Fe (about 8 times) is seriously improved compared with pure HA material (about 2 times) during the change-discharge process. The capacity retention ratio of HA-Fe is 55.63% when the current density increased from 0.05 A·g-1 to 1 A·g-1, which is higher than that of HA (32.55%) and Fe (24.85%). In the end, the storage mechanism of HA-Fe was investigated with ex-situ XPS measurements, and it was found that the C=O and C=C bonds are the activation sites for storage Li ions but have different redox voltages.

A generalizable and interpretable model for mortality risk stratification of sepsis patients in intensive care unit.

PURPOSE: This study aimed to construct a mortality model for the risk stratification of intensive care unit (ICU) patients with sepsis by applying a machine learning algorithm. METHODS: Adult patients who were diagnosed with sepsis during admission to ICU were extracted from MIMIC-III, MIMIC-IV, eICU, and Zigong databases. MIMIC-III was used for model development and internal validation. The other three databases were used for external validation. Our proposed model was developed based on the Extreme Gradient Boosting (XGBoost) algorithm. The generalizability, discrimination, and validation of our model were evaluated. The Shapley Additive Explanation values were used to interpret our model and analyze the contribution of individual features. RESULTS: A total of 16,741, 15,532, 22,617, and 1,198 sepsis patients were extracted from the MIMIC-III, MIMIC-IV, eICU, and Zigong databases, respectively. The proposed model had an area under the receiver operating characteristic curve (AUROC) of 0.84 in the internal validation, which outperformed all the traditional scoring systems. In the external validations, the AUROC was 0.87 in the MIMIC-IV database, better than all the traditional scoring systems; the AUROC was 0.83 in the eICU database, higher than the Simplified Acute Physiology Score III and Sequential Organ Failure Assessment (SOFA),equal to 0.83 of the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV), and the AUROC was 0.68 in the Zigong database, higher than those from the systemic inflammatory response syndrome and SOFA. Furthermore, the proposed model showed the best discriminatory and calibrated capabilities and had the best net benefit in each validation. CONCLUSIONS: The proposed algorithm based on XGBoost and SHAP-value feature selection had high performance in predicting the mortality of sepsis patients within 24 h of ICU admission.

Data-driven decision-making for precision diagnosis of digestive diseases.

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Characteristics and Outcomes of De Novo Genitourinary Malignancy in Solid Organ Transplant Recipients at the University of Minnesota.

BACKGROUND: Studies examining outcomes of genitourinary malignancy (GU) in the solid organ transplant (SOT) population predominantly focus on renal transplant recipients and consist of relatively small cohorts. We aimed to expand knowledge of the characteristics and outcomes of de novo GU malignancies in all patients with SOT at a large tertiary center. METHODS: The SOT database was queried for recipients with de novo bladder, renal cell, and prostate malignancy, and a retrospective chart review was performed. Descriptive statistics and Kaplan-Meier survival estimates were calculated. Cox proportional hazards regression was used for multivariate modeling of predictive factors in the development of GU malignancy. RESULTS: Solid organ transplant recipients with de novo bladder malignancy comprised 64.3% with high grade and 38.1% with advanced stage (≥T2) disease at initial diagnosis. Only 3.7% of patients with de novo renal cell carcinoma presented with metastatic disease, and 13.6% with localized disease developed recurrences. The most common stage in de novo prostate cancer patients was pT3 (52.2%). Kaplan-Meier estimates (95% CI) for 5-year overall (OS) and cancer-specific survival (CSS) were 44.12% (31.13-62.52) and 80.80% (68.85-94.81) for bladder, 78.90% (68.93-90.30) and 96.61% (92.10-100.00) for renal cell, and 81.18% (72.01-91.51) and 96.16% (90.95-100.00) for prostate cancer, respectively. Age at transplant and time from transplant to cancer diagnosis were predictive of de novo bladder cancer OS (P = .042 and .021, respectively). CONCLUSION: To our knowledge, this is the largest single-center cohort examined for GU malignancy after SOT. Bladder and renal cell cancer had worse OS but similar CSS as historical rates for nontransplant patients. De novo prostate cancer had similar CSS.