Deep learning-driven hybrid model for short-term load forecasting and smart grid information management.

Accurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with the large-scale and high-dimensional energy information, present challenges in handling intricate dynamic features and long-term dependencies. This paper proposes a computational approach to address these challenges in short-term power load forecasting and energy information management, with the goal of accurately predicting future load demand. The study introduces a hybrid method that combines multiple deep learning models, the Gated Recurrent Unit (GRU) is employed to capture long-term dependencies in time series data, while the Temporal Convolutional Network (TCN) efficiently learns patterns and features in load data. Additionally, the attention mechanism is incorporated to automatically focus on the input components most relevant to the load prediction task, further enhancing model performance. According to the experimental evaluation conducted on four public datasets, including GEFCom2014, the proposed algorithm outperforms the baseline models on various metrics such as prediction accuracy, efficiency, and stability. Notably, on the GEFCom2014 dataset, FLOP is reduced by over 48.8%, inference time is shortened by more than 46.7%, and MAPE is improved by 39%. The proposed method significantly enhances the reliability, stability, and cost-effectiveness of smart grids, which facilitates risk assessment optimization and operational planning under the context of information management for smart grid systems.

Squaramide-catalyzed enantioselective Michael addition of nitromethane to 2-enoylazaarenes: synthesis of chiral azaarene-containing γ-nitroketones.

Bifunctional chiral squaramide-catalyzed highly enantioselective Michael addition of nitromethane to diverse 2-enoylazaarenes was successfully performed. This protocol provided a set of chiral azaarene-containing γ-nitroketones with up to 98% yield and 98% ee in a solvent-free catalytic system under mild conditions. Furthermore, gram-scale synthetic utility was also showcased.

Liver cancer from the perspective of single-cell sequencing: a review combined with bibliometric analysis.

BACKGROUND: Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics. METHOD: Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis. RESULTS: A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'. CONCLUSION: This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.

BACKGROUND: Major depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods for accurately predicting MDD in patients with NT1. OBJECTIVE: This study utilized machine learning (ML) algorithms to identify critical variables and developed the prediction model for predicting MDD in patients with NT1. METHODS: The study included 267 NT1 patients from four sleep centers. The diagnosis of comorbid MDD was based on Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5). ML models, including six full models and six compact models, were developed using a training set. The performance of these models was compared in the testing set, and the optimal model was evaluated in the testing set. Various evaluation metrics, such as Area under the receiver operating curve (AUC), precision-recall (PR) curve and calibration curve were employed to assess and compare the performance of the ML models. Model interpretability was demonstrated using SHAP. RESULT: In the testing set, the logistic regression (LG) model demonstrated superior performance compared to other ML models based on evaluation metrics such as AUC, PR curve, and calibration curve. The top eight features used in the LG model, ranked by feature importance, included social impact scale (SIS) score, narcolepsy severity scale (NSS) score, total sleep time, body mass index (BMI), education years, age of onset, sleep efficiency, sleep latency. CONCLUSION: The study yielded a straightforward and practical ML model for the early identification of MDD in patients with NT1. A web-based tool for clinical applications was developed, which deserves further verification in diverse clinical settings.

KDM3B inhibitors disrupt the oncogenic activity of PAX3-FOXO1 in fusion-positive rhabdomyosarcoma.

Fusion-positive rhabdomyosarcoma (FP-RMS) is an aggressive pediatric sarcoma driven primarily by the PAX3-FOXO1 fusion oncogene, for which therapies targeting PAX3-FOXO1 are lacking. Here, we screen 62,643 compounds using an engineered cell line that monitors PAX3-FOXO1 transcriptional activity identifying a hitherto uncharacterized compound, P3FI-63. RNA-seq, ATAC-seq, and docking analyses implicate histone lysine demethylases (KDMs) as its targets. Enzymatic assays confirm the inhibition of multiple KDMs with the highest selectivity for KDM3B. Structural similarity search of P3FI-63 identifies P3FI-90 with improved solubility and potency. Biophysical binding of P3FI-90 to KDM3B is demonstrated using NMR and SPR. P3FI-90 suppresses the growth of FP-RMS in vitro and in vivo through downregulating PAX3-FOXO1 activity, and combined knockdown of KDM3B and KDM1A phenocopies P3FI-90 effects. Thus, we report KDM inhibitors P3FI-63 and P3FI-90 with the highest specificity for KDM3B. Their potent suppression of PAX3-FOXO1 activity indicates a possible therapeutic approach for FP-RMS and other transcriptionally addicted cancers.

Identification of molecular characteristics of FUT8 and alteration of core fucosylation in kidney renal clear cell cancer.

BACKGROUND: Kidney renal clear cell cancer (KIRC) is a type of urological cancer that occurs worldwide. Core fucosylation (CF), as the most common post-translational modification, is involved in the tumorigenesis. METHODS: The alterations of CF-related genes were summarized in pan-cancer. The "ConsensusClusterPlus" package was utilized to identify two CF-related KIRC subtypes. The "ssgsea" function was chosen to estimate the CF score, signaling pathways and cell deaths. Multiple algorithms were applied to assess immune responses. The "oncoPredict" was utilized to estimate the drug sensitivity. The IHC and subgroup analysis was performed to reveal the molecular features of FUT8. Single-cell RNA sequencing (scRNA-seq) data were scrutinized to evaluate the CF state. RESULTS: In pan-cancer, there was a noticeable alteration in the expression of CF-related genes. In KIRC, two CF-related subtypes (i.e., C1, C2) were obtained. In comparison to C2, C1 exhibited a higher CF score and correlated with poorer overall survival. Additionally, the TME of C2 demonstrated increased activity in neutrophils, macrophages, myeloid dendritic cells, and B cells, alongside a higher presence of silent mast cells, NK cells, and endothelial cells. Compared to normal samples, higher expression of FUT8 is observed in KIRC. The mutation of SETD2 was more frequent in low-FUT8 samples while the mutation of DNAH9 was more frequent in high-FUT8 samples. scRNA-seq analyses revealed that the CF score was predominantly higher in endothelial cells and fibroblast cells. CONCLUSIONS: Two CF-related subtypes with distinct prognosis and TME were identified in KIRC. FUT8 exhibited elevated expression in KIRC samples.

Clinical influencing factors affecting pulmonary hypertension in hemodialysis patients

Background: The fluid status and rate of blood flow through the arteriovenous fistula (AVF) are two important factors affecting hemodynamic in hemodialysis patients; however, their effects on pulmonary hypertension have rarely been studied. Hence, we aimed to evaluate the effects of these factors in hemodialysis patients with pulmonary hypertension. Methods: This single-center cross-sectional survey included 219 maintenance hemodialysis patients (139 [63.5%] male). The prevalence of pulmonary hypertension was 13.6% (30 of 219). Pulmonary artery pressure was measured by echocardiography, fluid status was measured objectively using bioimpedance spectroscopy, and blood flow rate in the AVF (Qa) was determined using Doppler ultrasound. Results: The overall mean overhydration before hemodialysis was 1.5 L (range, 0.6-2.8 L). The mean overhydration in patients with and without pulmonary hypertension was 3.6 L (range, 2.3-4.6 L) and 1.4 L (range, 0.6-2.4 L), respectively (p < 0.001). The overall mean Qa was 780 mL/min (range, 570-1,015.5 mL/min). The mean Qa of patients with and without pulmonary hypertension was 672 mL/min (range, 505.7-982.2 mL/min) and 790 mL/min (range, 591-1,026 mL/min), respectively (p = 0.27). Overhydration (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.08-1.97; p = 0.01), N-terminal prohormone of brain natriuretic peptide (NT-proBNP; OR, 1.36; 95% CI, 1.09-1.71; p = 0.007), and left atrial diameter (OR, 1.14; 95% CI, 1.01-1.28; p = 0.03) were risk factors. Conclusion: Pulmonary hypertension is strongly associated with overhydration, NT-proBNP, and left atrial diameter in hemodialysis patients.

Zinc-based biomaterials for bone repair and regeneration: mechanism and applications.

Zinc (Zn) is one of the most important trace elements in the human body and plays a key role in various physiological processes, especially in bone metabolism. Zn-containing materials have been reported to enhance bone repair through promoting cell proliferation, osteogenic activity, angiogenesis, and inhibiting osteoclast differentiation. Therefore, Zn-based biomaterials are potential substitutes for traditional bone grafts. In this review, the specific mechanisms of bone formation promotion by Zn-based biomaterials were discussed, and recent developments in their application in bone tissue engineering were summarized. Moreover, the challenges and perspectives of Zn-based biomaterials were concluded, revealing their attractive potential and development directions in the future.

Combined inhibition of topoisomerase I and poly(ADP-ribose) polymerase: A synergistic therapeutic strategy for glioblastoma with phosphatase and tensin homolog deficiency.

Background: Deletions or loss-of-function mutations in phosphatase and tensin homolog (PTEN) are common in glioblastoma (GBM) and have been associated with defective DNA damage repair. Here we investigated whether PTEN deficiency presents a vulnerability to a simultaneous induction of DNA damage and suppression of repair mechanisms by combining topoisomerase I (TOP1) and PARP inhibitors. Methods: Patient-derived GBM cells and isogenic PTEN-null and PTEN-WT glioma cells were treated with LMP400 (Indotecan), a novel non-camptothecin TOP1 inhibitor alone and in combination with a PARP inhibitor, Olaparib or Niraparib. RNAseq analysis was performed to identify treatment-induced dysregulated pathways. Results: We found that GBM cells lacking PTEN expression are highly sensitive to LMP400; however, rescue of the PTEN expression reduces sensitivity to the treatment. Combining LMP400 with Niraparib leads to synergistic cytotoxicity by inducing G2/M arrest, DNA damage, suppression of homologous recombination-related proteins, and activation of caspase 3/7 activity significantly more in PTEN-null cells compared to PTEN-WT cells. LMP400 and Niraparib are not affected by ABCB1 and ABCG2, the major ATP-Binding Cassette (ABC) drug efflux transporters expressed at the blood-brain barrier (BBB), thus suggesting BBB penetration which is a prerequisite for potential brain tumor treatment. Animal studies confirmed both an anti-glioma effect and sufficient BBB penetration to prolong survival of mice treated with the drug combination. Conclusions: Our findings provide a proof of concept for the combined treatment with LMP400 and Niraparib in a subset of GBM patients with PTEN deficiency.

Piperacetazine Directly Binds to the PAX3::FOXO1 Fusion Protein and Inhibits Its Transcriptional Activity.

The tumor-specific chromosomal translocation product, PAX3::FOXO1, is an aberrant fusion protein that plays a key role for oncogenesis in the alveolar subtype of rhabdomyosarcoma (RMS). PAX3::FOXO1 represents a validated molecular target for alveolar RMS and successful inhibition of its oncogenic activity is likely to have significant clinical applications. Even though several PAX3::FOXO1 function-based screening studies have been successfully completed, a directly binding small-molecule inhibitor of PAX3::FOXO1 has not been reported. Therefore, we screened small-molecule libraries to identify compounds that were capable of directly binding to PAX3::FOXO1 protein using surface plasmon resonance technology. Compounds that directly bound to PAX3::FOXO1 were further evaluated in secondary transcriptional activation assays. We discovered that piperacetazine can directly bind to PAX3::FOXO1 protein and inhibit fusion protein-derived transcription in multiple alveolar RMS cell lines. Piperacetazine inhibited anchorage-independent growth of fusion-positive alveolar RMS cells but not embryonal RMS cells. On the basis of our findings, piperacetazine is a molecular scaffold upon which derivatives could be developed as specific inhibitors of PAX3::FOXO1. These novel inhibitors could potentially be evaluated in future clinical trials for recurrent or metastatic alveolar RMS as novel targeted therapy options. SIGNIFICANCE: RMS is a malignant soft-tissue tumor mainly affecting the pediatric population. A subgroup of RMS with worse prognosis harbors a unique chromosomal translocation creating an oncogenic fusion protein, PAX3::FOXO1. We identified piperacetazine as a direct inhibitor of PAX3::FOXO1, which may provide a scaffold for designing RMS-specific targeted therapy.

Loss of FUT8 in renal tubules ameliorates ischemia-reperfusion injury-induced renal interstitial inflammation transition to fibrosis via the TLR3-NF-κB pathway.

Renal ischemia-reperfusion injury (IRI) is a common reason of acute kidney injury (AKI). AKI can progress to chronic kidney disease (CKD) in some survivors. Inflammation is considered the first-line response to early-stage IRI. We previously reported that core fucosylation (CF), specifically catalyzed by α-1,6 fucosyltransferase (FUT8), exacerbates renal fibrosis. However, the FUT8 characteristics, role, and mechanism in inflammation and fibrosis transition remain unclear. Considering renal tubular cells are the trigger cells that initiate the fibrosis in the AKI-to-CKD transition in IRI, we targeted CF by generating a renal tubular epithelial cell (TEC)-specific FUT8 knockout mouse and measured FUT8-driven and downstream signaling pathway expression and AKI-to-CKD transition. During the IRI extension phase, specific FUT8 deletion in the TECs ameliorated the IRI-induced renal interstitial inflammation and fibrosis mainly via the TLR3 CF-NF-κB signaling pathway. The results firstly indicated the role of FUT8 in the transition of inflammation and fibrosis. Therefore, the loss of FUT8 in TECs may be a novel potential strategy for treating AKI-CKD transition.

CTLA4-Ig protects tacrolimus-induced oxidative stress via inhibiting the AKT/FOXO3 signaling pathway in rats.

BACKGROUND/AIMS: Although the conversion from tacrolimus (TAC) to cytotoxic T-lymphocyte-associated antigen 4-immunoglobulin (CTLA4-Ig) is effective in reducing TAC-induced nephrotoxicity, it remains unclear whether CTLA4-Ig has a direct effect on TAC-induced renal injury. In this study, we evaluated the effects of CTLA4-Ig on TAC-induced renal injury in terms of oxidative stress. METHODS: In vitro study was performed to assess the effect of CTLA4-Ig on TAC-induced cell death, reactive oxygen species (ROS), apoptosis, and the protein kinase B (AKT)/forkhead transcription factor (FOXO) 3 pathway in human kidney 2 cells. In the in vivo study, the effect of CTLA4-Ig on TAC-induced renal injury was evaluated using renal function, histopathology, markers of oxidative stress (8-hydroxy-2'-deoxyguanosine) and metabolites (4-hydroxy-2-hexenal, catalase, glutathione S-transferase, and glutathione reductase), and activation of the AKT/FOXO3 pathway with insulin-like growth factor 1 (IGF-1). RESULTS: CTLA4-Ig significantly decreased cell death, ROS, and apoptosis caused by TAC. TAC treatment increased apoptotic cell death and apoptosis-related proteins (increased Bcl-2-associated X protein and caspase-3 and decreased Bcl-2), but it was reversed by CTLA4-Ig treatment. The activation of p-AKT and p-FOXO3 by TAC decreased with CTLA4-Ig treatment. TAC-induced renal dysfunction and oxidative marker levels were significantly improved by CTLA4-Ig in vivo. Concomitant IGF-1 treatment abolished the effects of CTLA4-Ig. CONCLUSION: CTLA4-Ig has a direct protective effect on TAC-induced renal injury via the inhibition of AKT/FOXO3 pathway.

The role of circadian clock-controlled mitochondrial dynamics in diabetic cardiomyopathy.

Diabetes mellitus is a metabolic disease with a high prevalence worldwide, and cardiovascular complications are the leading cause of mortality in patients with diabetes. Diabetic cardiomyopathy (DCM), which is prone to heart failure with preserved ejection fraction, is defined as a cardiac dysfunction without conventional cardiac risk factors such as coronary heart disease and hypertension. Mitochondria are the centers of energy metabolism that are very important for maintaining the function of the heart. They are highly dynamic in response to environmental changes through mitochondrial dynamics. The disruption of mitochondrial dynamics is closely related to the occurrence and development of DCM. Mitochondrial dynamics are controlled by circadian clock and show oscillation rhythm. This rhythm enables mitochondria to respond to changing energy demands in different environments, but it is disordered in diabetes. In this review, we summarize the significant role of circadian clock-controlled mitochondrial dynamics in the etiology of DCM and hope to play a certain enlightening role in the treatment of DCM.

Molecular Cytological Analysis and Specific Marker Development in Wheat-Psathyrostachys huashanica Keng 3Ns Additional Line with Elongated Glume.

Psathyrostachys huashanica Keng (2n = 2x = 14, NsNs) is an excellent gene resource for wheat breeding, which is characterized by early maturity, low plant height, and disease resistance. The wheat-P. huashanica derivatives were created by the elite genes of P. huashanica and permeate into common wheat through hybridization. Among them, a long-glume material 20JH1155 was identified, with larger grains and longer spike than its parents. In the present study, the methods of cytological observation, GISH, and sequential FISH analysis showed that 20JH1155 contained 21 pairs of wheat chromosomes and a pair of P. huashanica. There were some differences in 5A and 7B chromosomes between 20JH1155 and parental wheat 7182. Molecular marker, FISH, and sequence cloning indicated 20JH1155 alien chromosomes were 3Ns of P. huashanica. In addition, differentially expressed genes during immature spikelet development of 20JH1155 and 7182 and predicted transcription factors were obtained by transcriptome sequencing. Moreover, a total of 7 makers derived from Ph#3Ns were developed from transcriptome data. Taken together, the wheat-P. huashanica derived line 20JH1155 provides a new horizon on distant hybridization of wheat and accelerates the utilization of genes of P. huashanica.

Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease.

End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = - 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.

A stem cell epigenome is associated with primary nonresponse to CD19 CAR T cells in pediatric acute lymphoblastic leukemia.

CD19 chimeric antigen receptor T-cell therapy (CD19-CAR) has changed the treatment landscape and outcomes for patients with pre-B-cell acute lymphoblastic leukemia (B-ALL). Unfortunately, primary nonresponse (PNR), sustained CD19+ disease, and concurrent expansion of CD19-CAR occur in 20% of the patients and is associated with adverse outcomes. Although some failures may be attributable to CD19 loss, mechanisms of CD19-independent, leukemia-intrinsic resistance to CD19-CAR remain poorly understood. We hypothesize that PNR leukemias are distinct compared with primary sensitive (PS) leukemias and that these differences are present before treatment. We used a multiomic approach to investigate this in 14 patients (7 with PNR and 7 with PS) enrolled in the PLAT-02 trial at Seattle Children's Hospital. Long-read PacBio sequencing helped identify 1 PNR in which 47% of CD19 transcripts had exon 2 skipping, but other samples lacked CD19 transcript abnormalities. Epigenetic profiling discovered DNA hypermethylation at genes targeted by polycomb repressive complex 2 (PRC2) in embryonic stem cells. Similarly, assays of transposase-accessible chromatin-sequencing revealed reduced accessibility at these PRC2 target genes, with a gain in accessibility of regions characteristic of hematopoietic stem cells and multilineage progenitors in PNR. Single-cell RNA sequencing and cytometry by time of flight analyses identified leukemic subpopulations expressing multilineage markers and decreased antigen presentation in PNR. We thus describe the association of a stem cell epigenome with primary resistance to CD19-CAR therapy. Future trials incorporating these biomarkers, with the addition of multispecific CAR T cells targeting against leukemic stem cell or myeloid antigens, and/or combined epigenetic therapy to disrupt this distinct stem cell epigenome may improve outcomes of patients with B-ALL.

A New Risk Score to Predict Intensive Care Unit Admission for Patients with Acute Pancreatitis 48 Hours After Admission: Multicenter Study.

AIMS: The objective of this study was to develop and validate an easy-to-use risk score (APRS) to predict which patients with acute pancreatitis (AP) will need intensive care unit (ICU) treatment within 48 h post-hospitalization on the basis of the ubiquitously available clinical records. METHODS: Patients with acute pancreatitis were retrospectively included from three independent institutions (RM cohort, 5280; TJ cohort, 262; SN cohort, 196), with 56 candidate variables collected within 48 h post-hospitalization. The RM cohort was randomly divided into a training set (N = 4220) and a test set (N = 1060). The most predictive features were extracted by LASSO from the RM cohort and entered into multivariate analysis. APRS was constructed using the coefficients of the statistically significant variables weighted by the multivariable logistic regression model. The APRS was validated by RM, TJ, and SN cohorts. The C-statistic was employed to evaluate the APRS's discrimination. DeLong test was used to compare area under the receiver operating characteristic curve (AUC) differences. RESULTS: A total of 5738 patients with AP were enrolled. Eleven variables were selected by LASSO and entered into multivariate analysis. APRS was inferred using the above five factors (pleural effusion, ALT/AST, ALB/GLB, urea, and glucose) weighted by their regression coefficients in the multivariable logistic regression model. The C-statistics of APRS were 0.905 (95% CI 0.82-0.98) and 0.889 (95% CI 0.81-0.96) in RM and TJ validation. An online APRS web-based calculator was constructed to assist the clinician to earlier assess the clinical outcomes of patients with AP. CONCLUSION: APRS could effectively stratify patients with AP into high and low risk of ICU admission within 48 h post-hospitalization, offering clinical value in directing management and personalize therapeutic selection for patients with AP.

Machine learning model identifies aggressive acute pancreatitis within 48 h of admission: a large retrospective study.

BACKGROUND: Acute pancreatitis (AP) with critical illness is linked to increased morbidity and mortality. Current risk scores to identify high-risk AP patients have certain limitations. OBJECTIVE: To develop and validate a machine learning tool within 48 h after admission for predicting which patients with AP will develop critical illness based on ubiquitously available clinical, laboratory, and radiologic variables. METHODS: 5460 AP patients were enrolled. Clinical, laboratory, and imaging variables were collected within 48 h after hospital admission. Least Absolute Shrinkage Selection Operator with bootstrap method was employed to select the most informative variables. Five different machine learning models were constructed to predictive likelihood of critical illness, and the optimal model (APCU) was selected. External cohort was used to validate APCU. APCU and other risk scores were compared using multivariate analysis. Models were evaluated by area under the curve (AUC). The decision curve analysis was employed to evaluate the standardized net benefit. RESULTS: Xgboost was constructed and selected as APCU, involving age, comorbid disease, mental status, pulmonary infiltrates, procalcitonin (PCT), neutrophil percentage (Neu%), ALT/AST, ratio of albumin and globulin, cholinesterase, Urea, Glu, AST and serum total cholesterol. The APCU performed excellently in discriminating AP risk in internal cohort (AUC = 0.95) and external cohort (AUC = 0.873). The APCU was significant for biliogenic AP (OR = 4.25 [2.08-8.72], P < 0.001), alcoholic AP (OR = 3.60 [1.67-7.72], P = 0.001), hyperlipidemic AP (OR = 2.63 [1.28-5.37], P = 0.008) and tumor AP (OR = 4.57 [2.14-9.72], P < 0.001). APCU yielded the highest clinical net benefit, comparatively. CONCLUSION: Machine learning tool based on ubiquitously available clinical variables accurately predicts the development of AP, optimizing the management of AP.

An optimized bicistronic chimeric antigen receptor against GPC2 or CD276 overcomes heterogeneous expression in neuroblastoma.

Chimeric antigen receptor (CAR) T cell therapies targeting single antigens have performed poorly in clinical trials for solid tumors due to heterogenous expression of tumor-associated antigens (TAAs), limited T cell persistence, and T cell exhaustion. Here, we aimed to identify optimal CARs against glypican 2 (GPC2) or CD276 (B7-H3), which were highly but heterogeneously expressed in neuroblastoma (NB), a lethal extracranial solid tumor of childhood. First, we examined CAR T cell expansion in the presence of targets by digital droplet PCR. Next, using pooled competitive optimization of CAR by cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), termed P-COCC, we simultaneously analyzed protein and transcriptome expression of CAR T cells to identify high-activity CARs. Finally, we performed cytotoxicity assays to identify the most effective CAR against each target and combined the CARs into a bicistronic "OR" CAR (BiCisCAR). BiCisCAR T cells effectively eliminated tumor cells expressing GPC2 or CD276. Furthermore, the BiCisCAR T cells demonstrated prolonged persistence and resistance to exhaustion when compared with CARs targeting a single antigen. This study illustrated that targeting multiple TAAs with BiCisCAR may overcome heterogenous expression of target antigens in solid tumors and identified a potent, clinically relevant CAR against NB. Moreover, our multimodal approach integrating competitive expansion, P-COCC, and cytotoxicity assays is an effective strategy to identify potent CARs among a pool of candidates.

Core fucosylation involvement in the paracrine regulation of proteinuria-induced renal interstitial fibrosis evaluated with the use of a microfluidic chip.

Proteinuria is a clinical manifestation of chronic kidney disease that aggravates renal interstitial fibrosis (RIF), in which injury of peritubular microvessels is an important event. However, the changes in peritubular microvessels induced by proteinuria and their molecular mechanisms remain unclear. Thus, we aimed to develop a co-culture microfluidic device that contains renal tubules and peritubular microvessels to create a proteinuria model. We found that protein overload in the renal tubule induced trans-differentiation and apoptosis of endothelial cells (ECs) and pericytes. Moreover, profiling of secreted proteins in this model revealed that a paracrine network between tubules and microvessels was activated in proteinuria-induced microvascular injury. Multiple cytokine receptors in this paracrine network were core-fucosylated. Inhibition of core fucosylation significantly reduced ligand-receptor binding ability and blocked downstream pathways, alleviating trans-differentiation and apoptosis of ECs and pericytes. Furthermore, the protective effect of genetic FUT8 deficiency on proteinuria overload-induced RIF and pericyte-myofibroblast trans-differentiation was validated in FUT8 knockout heterozygous mice. In conclusion, we constructed and used a multiple-unit integrated microfluidic device to uncover the mechanism of proteinuria-induced RIF. Furthermore, FUT8 may serve as a hub-like therapeutic target to alleviate peritubular microvascular injury in RIF. STATEMENT OF SIGNIFICANCE: In this study, we constructed a multiple-unit integrated renal tubule-vascular chip. We reproduced human proteinuria on the chip and found that multiple receptors were modified by FUT8-catalyzed core fucosylation (CF) involved in the cross-talk between renal tubules and peritubular microvessels in proteinuria-induced RIF, and inhibiting the FUT8 of receptors could block the tubule-microvessel paracrine network and reverse the damage of peritubular microvessels and renal interstitial fibrosis. This tubule-vascular chip may provide a prospective platform to facilitate future investigations into the mechanisms of kidney diseases, and target-FUT8 inhibition may be an innovative and potential therapeutic strategy for RIF induced by proteinuria.