Bayesian modelling of time series data (BayModTS)-a FAIR workflow to process sparse and highly variable data.

MOTIVATION: Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in quantitative dynamical modelling is the integration of time series measurements, which often have high variability and low sampling resolution. Approaches are required to utilize such information while consistently handling uncertainties. RESULTS: We present BayModTS (Bayesian modelling of time series data), a new FAIR (findable, accessible, interoperable, and reusable) workflow for processing and analysing sparse and highly variable time series data. BayModTS consistently transfers uncertainties from data to model predictions, including process knowledge via parameterized models. Further, credible differences in the dynamics of different conditions can be identified by filtering noise. To demonstrate the power and versatility of BayModTS, we applied it to three hepatic datasets gathered from three different species and with different measurement techniques: (i) blood perfusion measurements by magnetic resonance imaging in rat livers after portal vein ligation, (ii) pharmacokinetic time series of different drugs in normal and steatotic mice, and (iii) CT-based volumetric assessment of human liver remnants after clinical liver resection. AVAILABILITY AND IMPLEMENTATION: The BayModTS codebase is available on GitHub at https://github.com/Systems-Theory-in-Systems-Biology/BayModTS. The repository contains a Python script for the executable BayModTS workflow and a widely applicable SBML (systems biology markup language) model for retarded transient functions. In addition, all examples from the paper are included in the repository. Data and code of the application examples are stored on DaRUS: https://doi.org/10.18419/darus-3876. The raw MRI ROI voxel data were uploaded to DaRUS: https://doi.org/10.18419/darus-3878. The steatosis metabolite data are published on FairdomHub: 10.15490/fairdomhub.1.study.1070.1.

Demonstrating Path-Independent Anyonic Braiding on a Modular Superconducting Quantum Processor.

Anyons, exotic quasiparticles in two-dimensional space exhibiting nontrivial exchange statistics, play a crucial role in universal topological quantum computing. One notable proposal to manifest the fractional statistics of anyons is the toric code model; however, scaling up its size through quantum simulation poses a serious challenge because of its highly entangled ground state. In this Letter, we demonstrate that a modular superconducting quantum processor enables hardware-pragmatic implementation of the toric code model. Through in-parallel control across separate modules, we generate a 10-qubit toric code ground state in four steps and realize six distinct braiding paths to benchmark the performance of anyonic statistics. The path independence of the anyonic braiding statistics is verified by correlation measurements in an efficient and scalable fashion. Our modular approach, serving as a hardware embodiment of the toric code model, offers a promising avenue toward scalable simulation of topological phases, paving the way for quantum simulation in a distributed fashion.

Retracted: Long Non-Coding RNA (lncRNA) SNHG5 Participates in Vertical Sleeve Gastrectomy for Type II Diabetes Mellitus by Regulating TGR5.

The Editors of Medical Science Monitor wish to inform you that the above manuscript has been retracted from publication due to concerns with the credibility and originality of the study, the manuscript content, and the Figure images. Reference: Weiwei Wei, Hao Tian, Xiandong Fu, Rongrong Yao, Dewang Su. Long Non-Coding RNA (lncRNA) SNHG5 Participates in Vertical Sleeve Gastrectomy for Type II Diabetes Mellitus by Regulating TGR5. Med Sci Monit, 2020; 26: e920628. DOI: 10.12659/MSM.920628.

Upconversion-Powered Photoelectrochemical Bioanalysis for DNA Sensing.

In this work, we report a new concept of upconversion-powered photoelectrochemical (PEC) bioanalysis. The proof-of-concept involves a PEC bionanosystem comprising a NaYF4:Yb,Tm@NaYF4 upconversion nanoparticles (UCNPs) reporter, which is confined by DNA hybridization on a CdS quantum dots (QDs)/indium tin oxide (ITO) photoelectrode. The CdS QD-modified ITO electrode was powered by upconversion absorption together with energy transfer effect through UCNPs for a stable photocurrent generation. By measuring the photocurrent change, the target DNA could be detected in a specific and sensitive way with a wide linear range from 10 pM to 1 µM and a low detection limit of 0.1 pM. This work exploited the use of UCNPs as signal reporters and realized upconversion-powered PEC bioanalysis. Given the diversity of UCNPs, we believe it will offer a new perspective for the development of advanced upconversion-powered PEC bioanalysis.

Organic Electrochemical Transistor with MoS2 Nanosheets Modified Gate Electrode for Sensitive Glucose Sensing.

An organic electrochemical transistor (OECT) with MoS2 nanosheets modified on the gate electrode was proposed for glucose sensing. MoS2 nanosheets, which had excellent electrocatalytic performance, a large specific surface area, and more active sites, were prepared by liquid phase ultrasonic exfoliation to modify the gate electrode of OECT, resulting in a large improvement in the sensitivity of the glucose sensor. The detection limit of the device modified with MoS2 nanosheets is down to 100 nM, which is 1~2 orders of magnitude better than that of the device without nanomaterial modification. This result manifests not only a sensitive and selective method for the detection of glucose based on OECT but also an extended application of MoS2 nanosheets for other biomolecule sensing with high sensitivity.

Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.

Nuclear magnetic resonance (NMR) is a crucial technique for analyzing mixtures consisting of small molecules, providing non-destructive, fast, reproducible, and unbiased benefits. However, it is challenging to perform mixture identification because of the offset of chemical shifts and peak overlaps that often exist in mixtures such as plant flavors. Here, we propose a deep-learning-based mixture identification method (DeepMID) that can be used to identify plant flavors (mixtures) in a formulated flavor (mixture consisting of several plant flavors) without the need to know the specific components in the plant flavors. A pseudo-Siamese convolutional neural network (pSCNN) and a spatial pyramid pooling (SPP) layer were used to solve the problems due to their high accuracy and robustness. The DeepMID model is trained, validated, and tested on an augmented data set containing 50,000 pairs of formulated and plant flavors. We demonstrate that DeepMID can achieve excellent prediction results in the augmented test set: ACC = 99.58%, TPR = 99.48%, FPR = 0.32%; and two experimentally obtained data sets: one shows ACC = 97.60%, TPR = 92.81%, FPR = 0.78% and the other shows ACC = 92.31%, TPR = 80.00%, FPR = 0.00%. In conclusion, DeepMID is a reliable method for identifying plant flavors in formulated flavors based on NMR spectroscopy, which can assist researchers in accelerating the design of flavor formulations.

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures.

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.

Long Non-Coding RNA (lncRNA) SNHG5 Participates in Vertical Sleeve Gastrectomy for Type II Diabetes Mellitus by Regulating TGR5.

BACKGROUND Due to its remarkable effect in controlling glycometabolism, relatively simple operation, and low risk of complications, sleeve gastrectomy (SG) has become the preferred surgical treatment for type II diabetes mellitus. Increased blood glucose in the body can cause damage to functional cells. MATERIAL AND METHODS Long non-coding RNA SNHG5 expression and TGR5 in serum were analyzed by real-time PCR. A diabetic cell model was established by culturing normal human intestinal epithelial cells NCM460 and DLD-1 with high-glucose and high-fat medium. CCK-8 assay, TUNEL assay, and flow cytometry were used to assess cell growth and apoptosis, respectively. The secretion of lactate dehydrogenase (LDH) was detected using the LDH Cytotoxicity Kit. lncRNA SNHG5 was downregulated by siRNA. The changes in expression of SNHG5, TGR5, Akt, p65, and Bcl-2 were analyzed by real-time PCR assay or Western blot. RESULTS In 40 type II diabetes patients who underwent sleeve gastrectomy, the expression of SNHG5 decreased and the expression of TGR5 increased compared with that before the operation. After high-glucose and high-fat culture, cell growth was inhibited and cell apoptosis increased significantly. The expression of SNHG5 was increased and TGR5 was decreased with high-glucose and high-fat culture. However, high glucose and high fat showed an opposite trend for cell growth, apoptosis, and LDH release under inhibition of SNHG5. The expression levels of TGR5 and Akt, p65, and Bcl-2 were also returned to normal by SNHG5 inhibition. CONCLUSIONS By downregulating expression of the SNHG5 gene and then altering expression of the TGR5 gene, the damage to colorectal cells induced by high glucose was alleviated. This may be one of the mechanisms underlying the effect of sleeve gastric surgery in treatment of diabetes mellitus.

Asymmetric Boron-Cored Aggregation-Induced Emission Luminogen with Multiple Functions Synthesized through Stepwise Conversion from a Symmetric Ligand.

Multifunction luminogens have emerged as promising candidates in high-performance sensor and imaging systems. Concise approaches to the synthesis of such molecules are urgently required both for fundamental research and technological applications. In this study, a new symmetric ligand of di(2-hydroxyphenyl)phthalazine with multiple binding sites around a phthalazine unit was readily synthesized, which could be converted efficiently into an asymmetric luminogen (OBN-DHPP) through the formation of oxygen-boron-nitrogen bonding. This molecule has a twistable π-extended backbone with a tetracoordinated boron core bearing two bulky phenyl groups, giving it abundant optical properties including a large Stokes shift piezochromism and aggregation-induced emission enhancement. Importantly, the presence of a free phenolic hydroxyl group in the backbone of OBN-DHPP enables the incorporation of various functional moieties into the asymmetric luminogen. As an example, polyethylene glycol (PEG)-modified luminogen (OBN-DHPP-PEG45) was synthesized. In the aqueous medium, OBN-DHPP-PEG45 could self-assemble into spherical nanoparticles with low cytotoxicity and excellent emission performance as well as high solubility. The results of flow cytometry and fluorescence microscopy reveal that these nanoparticles could be internalized successfully by HeLa cells, demonstrating their potential application in bioimaging.

[Preliminary study on pathogen of Whitmania pigra disease in high temperature environment].

In this paper, on the contrast of healthy leech, the bacterial diversities were analyzed by 16S rDNA sequence analysis of the bacteria of muscle and intestinal tract of Whitmania pigra, the environment water and sediment of cultivating the diseased Wh. pigra in high temperature by high-throughput sequencing to determine the possible pathogenic bacteria of bacterial diseases of Leech in high temperature. The results showed that the original sequence reached over 83 000, and the effective sequences accounted for more than 87%. The GC contents ranged from 52% to 54% and the bacterial diversities were abundant. Bacterial relative abundance analysis showed that the bacterial content of Proteobacteria, Bacteroidetes, and Firmicutes was the most abundant in all treatments. Compared with healthy leech muscles and intestines, the muscle and intestinal tract of pathogenic leech relative abundance of Bacteroides, Pseudomonas, and Desulfovibrio was significantly increased, and it was abundant in water and sediment of diseased leeches, Lead to the possibility that the pathogenic bacteria of this bacterial disease may be Bacteroides, Pseudomonas, Desulfovibrio.

Cu/Pd cooperatively catalyzed tandem C-N and C-P bond formation: access to phosphorated 2H-indazoles.

A novel Cu/Pd cooperatively catalyzed tandem C-N and C-P bond formation reaction between 2-alkynyl azobenzenes and P(O)H compounds has been developed. This reaction provides a convenient approach for the synthesis of various phosphorated 2H-indazoles in moderate to good yields, exhibiting good functional group tolerance and high atom economy.

A Novel Organic Electrochemical Transistor-Based Platform for Monitoring the Senescent Green Vegetative Phase of Haematococcus pluvialis Cells.

The freshwater unicellular microalga Haematococcus pluvialis (H. pluvialis) has gained increasing attention because of its high-value metabolite astaxanthin, a super anti-oxidant. For the maximum astaxanthin production, a key problem is how to determine the senescent green vegetative phase of H. pluvialis cells to apply the astaxanthin production inducers. The conventional methods are time-consuming and laborious. In this study, a novel platform based on organic electrochemical transistor (OECT) was produced. A significant channel current change of OECTs caused by settled H. pluvialis cells on the poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT: PSS) film was recorded commencing from 75 min and a stationary stage was achieved at 120 min after the combined treatment of blue light irradiation and sodium bicarbonate solution additives, which indicate the onset and maturation of the senescent green vegetative phase, respectively. Therefore, the appropriate time point (120 min after sample loading) to apply astaxanthin production inducers was determined by as-fabricated OECTs. This work may assist to develop a real-time biosensor to indicate the appropriate time to apply inducers for a maximum astaxanthin production of H. pluvialis cells.

Identification of Proteins Interacting with Cytoplasmic High-Mobility Group Box 1 during the Hepatocellular Response to Ischemia Reperfusion Injury.

Ischemia/reperfusion injury (IRI) occurs inevitably in liver transplantations and frequently during major resections, and can lead to liver dysfunction as well as systemic disorders. High-mobility group box 1 (HMGB1) plays a pathogenic role in hepatic IRI. In the normal liver, HMGB1 is located in the nucleus of hepatocytes; after ischemia reperfusion, it translocates to the cytoplasm and it is further released to the extracellular space. Unlike the well-explored functions of nuclear and extracellular HMGB1, the role of cytoplasmic HMGB1 in hepatic IRI remains elusive. We hypothesized that cytoplasmic HMGB1 interacts with binding proteins involved in the hepatocellular response to IRI. In this study, binding proteins of cytoplasmic HMGB1 during hepatic IRI were identified. Liver tissues from rats with warm ischemia reperfusion (WI/R) injury and from normal rats were subjected to cytoplasmic protein extraction. Co-immunoprecipitation using these protein extracts was performed to enrich HMGB1-protein complexes. To separate and identify the immunoprecipitated proteins in eluates, 2-dimensional electrophoresis and subsequent mass spectrometry detection were performed. Two of the identified proteins were verified using Western blotting: betaine-homocysteine S-methyltransferase 1 (BHMT) and cystathionine γ-lyase (CTH). Therefore, our results revealed the binding of HMGB1 to BHMT and CTH in cytoplasm during hepatic WI/R. This finding may help to better understand the cellular response to IRI in the liver and to identify novel molecular targets for reducing ischemic injury.

Involvement of human chorionic gonadotropin in regulating vasculogenic mimicry and hypoxia-inducible factor-1α expression in ovarian cancer cells.

BACKGROUND: Human chorionic gonadotropin (hCG) can play a crucial role in angiogenesis. In the present study, we focused on hCG to gain insight into its potential effects on vasculogenic mimicry (VM) in ovarian cancer cells. METHODS: Ovarian cancer OVCAR-3 cells were incubated with different concentrations of recombinant hCG in 3-dimensional cultures. VM was identified by morphological observations and vascular endothelial cell marker detection in OVCAR-3 cells. Expression of hCG, hypoxia-inducible factor-1α (HIF-1α), and the endothelial cell markers CD31, VEGF, and factor VIII were detected by reverse transcription polymerase chain reaction and western blotting. The effect of hCG on endothelial cell-marker expression in ovarian cancer cells was further explored using small interfering RNA (siRNA) and plasmid-based approaches. RESULTS: Incubation of OVCAR-3 cells with recombinant hCG induced vessel-like network formation, which was accompanied by significant elevation of vascular marker expression. Attenuation of hCG expression by siRNA in OVCAR-3 cells suppressed the expression of endothelial cell markers and HIF-1α by tumour cells. Overexpression of hCG in OVCAR-3 cells resulted in increased expression of endothelial cell markers and HIF-1α. CONCLUSIONS: HCG was crucial for changing the phenotype of OVCAR-3 cells to endothelial-like cells. The effect of hCG induction on VM in ovarian cancer cells is potentially associated with HIF-1α.

Laparoscopic Nerve-Sparing Radical Hysterectomy for Cervical Carcinoma: Emphasis on Nerve Content in Removed Cardinal Ligaments.

OBJECTIVE: To evaluate the histopathology of autonomic nerve removal within the cardinal ligaments (CLs), patients' postoperative urinary function, and the feasibility and safety of laparoscopic nerve-sparing radical hysterectomy (LNSRH) for treatment of early-stage cervical cancer. METHODS: Perioperative and postoperative parameters were compared between patients with biopsy-proven, early-stage cervical carcinoma treated with LNSRH (n = 64) versus those treated with laparoscopic radical hysterectomy (LRH, n = 42) in a retrospective study. Nerves within CLs were identified by hematoxylin-eosin staining. Rates of the following complications were compared: bladder function, sexual dysfunction, and defecation problems. RESULTS: Duration of surgery, intraoperative blood loss, duration of hospitalization, and morbidity did not differ significantly between the LNSRH and LRH groups. Patients who underwent LNSRH had a significantly earlier return of bladder and bowel functions, with an average time to achieve residual urine of 50 mL or less of 10.22 days and a mean first defecation time of 3.58 days. Nerves were observed mainly in the CLs of the LRH group. Disease-free survival rate did not differ between the LNSRH (90.6%) and LRH (88.1%) groups (P = 0.643). CONCLUSIONS: The LNSRH is a safe, feasible, and easy procedure for trained laparoscopic surgeons. Patients who underwent LNSRH had a more satisfactory quality of life than patients who underwent LRH.

Intrahepatic Size Regulation in a Surgical Model: Liver Resection-Induced Liver Regeneration Counteracts the Local Atrophy following Simultaneous Portal Vein Ligation.

BACKGROUND/AIM: Liver size regulation is based on the balance between hepatic regeneration and atrophy. To achieve a better understanding of intrahepatic size regulation, we explored the size regulation of a portally deprived liver lobe on a liver subjected to concurrent portal vein ligation (PVL) and partial hepatectomy (PHx). MATERIALS AND METHODS: Using a surgical rat model consisting of right PVL (rPVL) plus 70% PHx, we evaluated the size regulation of liver lobes 1, 2, 3, and 7 days after the operation in terms of liver weight and hepatocyte proliferation. Portal hyperperfusion was confirmed by measuring portal flow. The portal vascular tree was visualized by injection of a contrast agent followed by CT imaging of explanted livers. Control groups consisted of 70% PHx, rPVL, and sham operation. RESULTS: The size of the ligated right lobe increased to 1.4-fold on postoperative day 7 when subjected to rPVL + 70% PHx. The right lobe increased to 3-fold when subjected to 70% PHx alone and decreased to 0.3-fold when subjected to rPVL only. The small but significant increase in liver weight after the combined procedure was accompanied by a low proliferative response. In contrast, hepatocyte proliferation was undetectable in the right lobe undergoing atrophy after PVL only. The caudate lobe in the rPVL + 70% PHx group increased to 4.6-fold, which is significantly more than in the other groups. This increase in liver weight was paralleled by persisting portal hyperperfusion and a prolonged proliferative phase of 3 days. CONCLUSIONS: A discontinued portal blood supply does not always result in atrophy of the ligated lobe. The concurrent regenerative stimulus induced by 70% PHx seemed to counteract the local atrophy after a simultaneously performed rPVL, leading to a low but prolonged regenerative response of the portally deprived liver lobe. This observation supports the conclusion that portal flow is not necessary for liver regeneration. The persisting portal hyperperfusion may be crucial for the specific kinetics of prolonged liver regeneration after rPVL + 70% PHx in the portally supplied caudate lobe. Both observations deserve more attention regarding the underlying mechanism in further studies.

Algorithmically generated rodent hepatic vascular trees in arbitrary detail.

Physiologically realistic geometric models of the vasculature in the liver are indispensable for modelling hepatic blood flow, the main connection between the liver and the organism. Current in vivo imaging techniques do not provide sufficiently detailed vascular trees for many simulation applications, so it is necessary to use algorithmic refinement methods. The method of Constrained Constructive Optimization (CCO) (Schreiner et al., 2006) is well suited for this purpose. Its results after calibration have been previously compared to experimentally acquired human vascular trees (Schwen and Preusser, 2012). The goal of this paper is to extend this calibration to the case of rodents (mice and rats), the most commonly used animal models in liver research. Based on in vivo and ex vivo micro-CT scans of rodent livers and their vasculature, we performed an analysis of various geometric features of the vascular trees. Starting from pruned versions of the original vascular trees, we applied the CCO procedure and compared these algorithmic results to the original vascular trees using a suitable similarity measure. The calibration of the postprocessing improved the algorithmic results compared to those obtained using standard CCO. In terms of angular features, the average similarity increased from 0.27 to 0.61, improving the total similarity from 0.28 to 0.40. Finally, we applied the calibrated algorithm to refine measured vascular trees to the (higher) level of detail desired for specific applications. Having successfully adapted the CCO algorithm to the rodent model organism, the resulting individual-specific refined hepatic vascular trees can now be used for advanced modeling involving, e.g., detailed blood flow simulations.

Rodent models and imaging techniques to study liver regeneration.

The liver has the unique capability of regeneration from various injuries. Different animal models and in vitro methods are used for studying the processes and mechanisms of liver regeneration. Animal models were established either by administration of hepatotoxic chemicals or by surgical approach. The administration of hepatotoxic chemicals results in the death of liver cells and in subsequent hepatic regeneration and tissue repair. Surgery includes partial hepatectomy and portal vein occlusion or diversion: hepatectomy leads to compensatory regeneration of the remnant liver lobe, whereas portal vein occlusion leads to atrophy of the ipsilateral lobe and to compensatory regeneration of the contralateral lobe. Adaptation of modern radiological imaging technologies to the small size of rodents made the visualization of rodent intrahepatic vascular anatomy possible. Advanced knowledge of the detailed intrahepatic 3D anatomy enabled the establishment of refined surgical techniques. The same technology allows the visualization of hepatic vascular regeneration. The development of modern histological image analysis tools improved the quantitative assessment of hepatic regeneration. Novel image analysis tools enable us to quantify reliably and reproducibly the proliferative rate of hepatocytes using whole-slide scans, thus reducing the sampling error. In this review, the refined rodent models and the newly developed imaging technology to study liver regeneration are summarized. This summary helps to integrate the current knowledge of liver regeneration and promises an enormous increase in hepatological knowledge in the near future.

[Effects of Different Pretreatment Methods on the Phenylketonuria Screening Model by FTIR/ATR Spectroscopy].

To establish a phenylketonuria screening model by FTIR/ATR spectroscopy, and to compare the effects of different pretreatment methods, such as baseline correction, smoothing, derivation, Fourier deconvolution, on the model quality. A consensus partial least squares regression method (cPLS) was used to build the quantitative model of phenylalanine in dried blood spots. The effects of different pretreatment methods on the model performance were investigated, using the correlation coefficient (r), root mean square error of prediction (RMSEP), mean relative error (MRE) and predictive accuracy (Acc). The nine-point smoothing coupled with the first differential was found to perform the best. Compared with the model by the original spectra, its r, RMSEP, MRE and Acc were improved from 0. 822 7, 115. 8, 0. 395 and 94. 6 to 0. 889 9, 102. 2, 0. 286 and 100, respectively. With the advantages of fast speed, easy process, no reagents consumption and environmental protection, the present method is expected to become a simple and green technology for rapidly screening the neonatal phenylketonuria in a large population.

Ischemic preconditioning protects against liver ischemia/reperfusion injury via heme oxygenase-1-mediated autophagy.

OBJECTIVES: Ischemic preconditioning exerts a protective effect in hepatic ischemia/reperfusion injury. The exact mechanism of ischemic preconditioning action remains largely unknown. Recent studies suggest that autophagy plays an important role in protecting against ischemia/reperfusion injury. However, the role of autophagy in ischemic preconditioning-afforded protection and its regulatory mechanisms in liver ischemia/reperfusion injury remain poorly understood. This study was designed to determine whether ischemic preconditioning could protect against liver ischemia/reperfusion injury via heme oxygenase-1-mediated autophagy. DESIGN: Laboratory investigation. SETTING: University animal research laboratory. SUBJECTS: Male inbred Lewis rats and C57BL/6 mice. INTERVENTIONS: Ischemic preconditioning was produced by 10 minutes of ischemia followed by 10 minutes of reperfusion prior to 60 minutes of ischemia. In a rat model of hepatic ischemia/reperfusion injury, rats were pretreated with wortmannin or rapamycin to evaluate the contribution of autophagy to the protective effects of ischemic preconditioning. Heme oxygenase-1 was inhibited with tin protoporphyrin IX. In a mouse model of hepatic ischemia/reperfusion injury, autophagy or heme oxygenase-1 was inhibited with vacuolar protein sorting 34 small interfering RNA or heme oxygenase-1 small interfering RNA, respectively. MEASUREMENTS AND MAIN RESULTS: Ischemic preconditioning ameliorated liver ischemia/reperfusion injury, as indicated by lower serum aminotransferase levels, lower hepatic inflammatory cytokines, and less severe ischemia/reperfusion-associated histopathologic changes. Ischemic preconditioning treatment induced autophagy activation, as indicated by an increase of LC3-II, degradation of p62, and accumulation of autophagic vacuoles in response to ischemia/reperfusion injury. When ischemic preconditioning-induced autophagy was inhibited with wortmannin in rats or vacuolar protein sorting 34-specific small interfering RNA in mice, liver ischemia/reperfusion injury was worsened, whereas rapamycin treatment increased autophagy and mimicked the protective effects of ischemic preconditioning. Furthermore, ischemic preconditioning increased heme oxygenase-1 expression. The inhibition of heme oxygenase-1 with tin protoporphyrin IX in rats or heme oxygenase-1-specific small interfering RNA in mice decreased ischemic preconditioning-induced autophagy and diminished the protective effects of ischemic preconditioning against ischemia/reperfusion injury. CONCLUSIONS: Ischemic preconditioning protects against liver ischemia/reperfusion injury, at least in part, via heme oxygenase-1-mediated autophagy.