A novel multivariable time series prediction model for acute kidney injury in general hospitalization.

OBJECTIVE: Early recognition and prevention are important to reduce the risk of acute kidney injury (AKI). We aimed to build a novel multivariate time series prediction model for dynamic AKI prediction in general hospitalization. METHODS: Deidentified electronic data of all patients admitted in Sichuan Provincial Peoples Hospital during 1 January 2019 and 31 December 2019 was retrospectively collected. Variables including demographics, admission variables, lab investigation variables and prescription variables were extracted. The first 50 most frequently detected lab investigation variables were selected as the predictive variables. Features within three previous days were selected to predict the risk of AKI in the next 24 h. The model was built using recurrent neural network (RNN) algorithm integrated with a time series convolution module and an attention convolution module and internally validated using five-fold cross-validation. Area under the ROC curve (AUC) and recall rate were used to evaluate the performance. The model was compared with four other models built using other machine learning algorithms and published machine learning models in literature. RESULTS: 47,960 eligible admissions were identified, among which 2694 (5.6%) admissions were complicated by AKI. Our model has an AUC of 0.908 and a recall rate of 0.869, outperforming models generated by mainstay machine learning methods and most of the published machine learning models. CONCLUSION: This study reports a novel machine learning prediction model for AKI in general hospitalization which is based on RNN algorithm. The model outperforms models generated by mainstay machine learning methods and most of the published machine learning models.

Precision control of mTORC1 is crucial for the maintenance and IL-13 responsiveness of alveolar macrophages.

Alveolar macrophages (AMs) are the lung resident macrophages critically involved in pulmonary homeostasis and immune response. Recent researches have uncovered a diversity of regulators responsible for the development, maintenance, and function of AMs. Nevertheless, the molecular underpinnings that determine the developmental and functional specification of AMs remain incompletely understood. Here, we investigated the role of the TSC1-mTOR pathway in murine AMs by genetic ablating Tsc1 or mTor alleles through Cd11c-Cre or LysM-Cre. Flow cytometry analyses revealed a prominent decrease in AMs in Tsc1f/f-Cd11c-Cre and Tsc1f/f/-LysM-Cre mice. Moreover, a reduction in AMs was also noted in mTorf/f-Cd11c-Cre or Rptorf/f-Cd11c-Cre mice. Further evidence implicated that elevation in cell death, most likely aberrant apoptosis or/and necroptosis, might be attributable to disrupted AM homeostasis. Whereas a diversity of cytokines involved in AM homeostasis and function triggered mTOR activation, only the IL-13 signaling, particularly Jak1 and Stat3 activation, was affected by TSC1 in macrophages. Further, select genes induced by IL-13, including AM surface markers such as Pparg, Fabp4/5, Nfil3 and Car4, and M2 hallmarks such as Arg1, Fizz, Ym1 and Clec7a were fine-tuned by the TSC1-mTOR pathway. Therefore, our results demonstrated that the TSC1-mTOR pathway has a crucial role in the homeostasis and functional specification of AMs through integrating cytokine signaling with metabolic cues.

Nanomaterials in electrochemical cytosensors.

Nano-electrochemical cytosensors have attracted intensive attention and achieved huge progress in the biomedical field owing to their stability, rapidity, accuracy, and low-cost properties. Currently, most nano-electrochemical cytosensors are prepared using metal nanoparticles or carbon nanomaterials. In application, the nano-electrochemical cytosensors immobilize a bio-sensitive substance on the electrode, and convert the target molecule and its reaction signal into an electrical signal through specific recognition between the biomolecules, thereby achieving detection. Using nano-electrochemical cytosensors can help diagnose disease quickly and accurately, which could contribute to early diagnosis and clinical analysis. In this review, we concentrate on the latest development in metal nanoparticle and carbon nanomaterial based nano-electrochemical cytosensors in the last three years. Finally, we summarize the development of cytosensors and propose the future development prospects.

TSC1/mTOR-controlled metabolic-epigenetic cross talk underpins DC control of CD8+ T-cell homeostasis.

Dendritic cells (DCs) play pivotal roles in T-cell homeostasis and activation, and metabolic programing has been recently linked to DC development and function. However, the metabolic underpinnings corresponding to distinct DC functions remain largely unresolved. Here, we demonstrate a special metabolic-epigenetic coupling mechanism orchestrated by tuberous sclerosis complex subunit 1 (TSC1)-mechanistic target of rapamycin (mTOR) for homeostatic DC function. Specific ablation of Tsc1 in the DC compartment (Tsc1DC-KO) largely preserved DC development but led to pronounced reduction in naïve and memory-phenotype cluster of differentiation (CD)8+ T cells, a defect fully rescued by concomitant ablation of mTor or regulatory associated protein of MTOR, complex 1 (Rptor) in DCs. Moreover, Tsc1DC-KO mice were unable to launch efficient antigen-specific CD8+ T effector responses required for containing Listeria monocytogenes and B16 melanomas. Mechanistically, our data suggest that the steady-state DCs tend to tune down de novo fatty acid synthesis and divert acetyl-coenzyme A (acetyl-CoA) for histone acetylation, a process critically controlled by TSC1-mTOR. Correspondingly, TSC1 deficiency elevated acetyl-CoA carboxylase 1 (ACC1) expression and fatty acid synthesis, leading to impaired epigenetic imprinting on selective genes such as major histocompatibility complex (MHC)-I and interleukin (IL)-7. Remarkably, tempering ACC1 activity was able to divert cytosolic acetyl-CoA for histone acetylation and restore the gene expression program compromised by TSC1 deficiency. Taken together, our results uncover a crucial role for TSC1-mTOR in metabolic programing of the homeostatic DCs for T-cell homeostasis and implicate metabolic-coupled epigenetic imprinting as a paradigm for DC specification.