Ischemia-free liver transplantation improves the prognosis of recipients using Functioned Marginal Liver grafts.

Background & Aims: The shortage of donor livers hinders the development of liver transplantations. This study aimed to clarify the poor outcomes of functioned marginal liver grafts (FMLs) and provide evidence for the improvement of ischemia-free liver transplantation (IFLT) on transplantation with FMLs. Methods: Propensity score matching was used to control for confounding factors. The outcomes of the control group and FMLs were compared to demonstrate the negative impact of FMLs in liver transplantation patients. We compared the clinical improvements of the different surgical types. To elucidate the underlying mechanism, we conducted bioinformatic analysis based on transcriptome and single-cell profiles. Results: FMLs showed a significantly higher Hazard Ratio (HR: 1.969, P = 0.018) than other marginal livers. A worse 90-days survival (12.3% vs. 5.0%, P = 0.007) was observed in patients who underwent FMLs. Patients receiving FMLs had a significant overall survival benefit after IFLT (10.4% vs. 31.3%, P = 0.006). Pyroptosis and inflammation are inhibited in patients who undergo IFLT. The infiltration of Natural Killer cells was lower in liver grafts from these patients. A positive relationship was observed between IL32 and Caspase 1 (R = 0.73, P = 0.01) and Gasdermin D (R = 0.84, P = 0.0012) in the bulk transcriptome profiles. Conclusion: FMLs function as a more important negative prognostic parameter than other marginal livers do. IFLT might ameliorate liver injury in FMLs by inhibiting the infiltration of NK cells, consequently leading to the abortion of IL-32, which drives pyroptosis in monocytes and macrophages.

Calibration transfer via filter learning.

BACKGROUND: Calibration transfer is an essential activity in analytical chemistry in order to avoid a complete recalibration. Currently, the most popular calibration transfer methods, such as piecewise direct standardization and dynamic orthogonal projection, require a certain amount of standard or reference samples to guarantee their effectiveness. To achieve higher efficiency, it is desirable to perform the transfer with as few reference samples as possible. RESULTS: To this end, we propose a new calibration transfer method by using a calibration database from a master instrument (source domain) and only one spectrum with known properties from a slave instrument (target domain). We first generate a counterpart of this spectrum in the source domain by a multivariate Gaussian kernel. Then, we train a filter to make the response function of the slave instrument equivalent to that of the master instrument. To avoid the need for labels from the target domain, we also propose an unsupervised way to implement our method. Compared with several state-of-the-art methods, the results on one simulated dataset and two real-world datasets demonstrate the effectiveness of our method. SIGNIFICANCE: Traditionally, the demand for certain amounts of reference samples during calibration transfer is cumbersome. Our approach, which requires only one reference sample, makes the transfer process simple and fast. In addition, we provide an alternative for performing unsupervised calibration transfer. As such, the proposed method is a promising tool for calibration transfer.

Identification of near-infrared characteristic bands of small bowel necrosis based on cellwise detection algorithm.

The near-infrared spectroscopy is often used to distinguish small bowel necrosis due to necrotizing enterocolitis (NEC). The characteristic bands of small bowel necrosis, as an important basis for evaluating the confidence of the differentiation results, are challenging to identify quickly. In this study, we proposed to identify characteristic bands of lesion samples based on hyperspectral imaging (HSI) and cellwise outlier detection. Rabbits were used as an animal model to simulate the clinical symptoms of NEC. The rabbits were detected at intervals of 10, 30, 60, and 90 min. The characteristic bands were identified within the same rabbit, between different rabbits and at different times. The result showed the bands near 763 nm, corresponding to the absorption peak of deoxyhemoglobin, were the characteristic bands separating samples with NEC. The identification result was plausible because hypoxia was the main cause of NEC. The method was easy to perform.

Automatic detection of ischemic necrotic sites in small intestinal tissue using hyperspectral imaging and transfer learning.

Acquiring large amounts of hyperspectral data of small intestinal tissue with real labels in the clinic is difficult, and the data shows inter-patient variability. Building an automatic identification model using a small dataset presents a crucial challenge in obtaining a strong generalization of the model. This study aimed to explore the performance of hyperspectral imaging and transfer learning techniques in the automatic identification of normal and ischemic necrotic sites in small intestinal tissue. Hyperspectral data of small intestinal tissues were collected from eight white rabbit samples. The transfer component analysis (TCA) method was performed to transfer learning on hyperspectral data between different samples and the variability of data distribution between samples was reduced. The results showed that the TCA transfer learning method improved the accuracy of the classification model with less training data. This study provided a reliable method for single-sample modelling to detect necrotic sites in small intestinal tissue .

A robust method to improve the regression accuracy of LIBS data: determination of heavy metal Cu in Tegillarca granosa.

Tegillarca granosa (T. granosa) is susceptible to contamination by heavy metals, which poses potential health risks for consumers. Laser-induced breakdown spectroscopy (LIBS) combined with the classical partial least squares (PLS) model has shown promise in determining heavy metal concentrations in T. granosa. However, the presence of outliers during calibration can compromise the model's integrity and diminish its predictive capabilities. To address this issue, we propose using a robust method for partial least squares, RSIMPLS, to improve the accuracy of Cu prediction in T. granosa. The RSIMPLS algorithm was employed to analyze and process the high-dimensional LIBS data and utilized diagnostic plots to identify various types of outliers. By selectively eliminating certain outliers, a robust calibration method was achieved. The results showed that LIBS spectroscopy has the potential to predict Cu in T. granosa, with a coefficient of determination (Rp2) of 0.79 and a root mean square error of prediction (RMSEP) of 11.28. RSIMPLS significantly improved the prediction accuracy of Cu concentrations with a 43% decrease in RMSEP compared to the PLS. These findings validated the effectiveness of combining LIBS data with the RSIMPLS algorithm for the prediction of Cu concentrations in T. granosa.

Novel ceRNA network construction associated with programmed cell death in acute rejection of heart allograft in mice.

Background: T cell-mediated acute rejection(AR) after heart transplantation(HT) ultimately results in graft failure and is a common indication for secondary transplantation. It's a serious threat to heart transplant recipients. This study aimed to explore the novel lncRNA-miRNA-mRNA networks that contributed to AR in a mouse heart transplantation model. Methods: The donor heart from Babl/C mice was transplanted to C57BL/6 mice with heterotopic implantation to the abdominal cavity. The control group was syngeneic heart transplantation with the same kind of mice donor. The whole-transcriptome sequencing was performed to obtain differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs) in mouse heart allograft. The biological functions of ceRNA networks was analyzed by GO and KEGG enrichment. Differentially expressed ceRNA involved in programmed cell death were further verified with qRT-PCR testing. Results: Lots of DEmRNAs, DEmiRNAs and DElncRNAs were identified in acute rejection and control after heart transplantation, including up-regulated 4754 DEmRNAs, 1634 DElncRNAs, 182 DEmiRNAs, and down-regulated 4365 DEmRNAs, 1761 DElncRNAs, 132 DEmiRNAs. Based on the ceRNA theory, lncRNA-miRNA-mRNA regulatory networks were constructed in allograft acute rejection response. The functional enrichment analysis indicate that the down-regulated mRNAs are mainly involved in cardiac muscle cell contraction, potassium channel activity, etc. and the up-regulated mRNAs are mainly involved in T cell differentiation and mononuclear cell migration, etc. The KEGG pathway enrichment analysis showed that the down-regulated DEmRNAs were mainly enriched in adrenergic signaling, axon guidance, calcium signaling pathway, etc. The up-regulated DEmRNAs were enriched in the adhesion function, chemokine signaling pathway, apoptosis, etc. Four lncRNA-mediated ceRNA regulatory pathways, Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox, 1700071M16Rik/miR-145a-3p/Themis2, were finally validated. In addition, increased expression of PVT1, 1700071M16Rik, Tox and Themis2 may be considered as potential diagnostic gene biomarkers in AR. Conclusion: We speculated that Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox and 1700071M16Rik/miR-145a-3p/Themis2 interaction pairs may serve as potential biomarkers in AR after HT.

Discrimination between normal and necrotic small intestinal tissue using hyperspectral imaging and unsupervised classification.

Objective and automatic clinical discrimination of normal and necrotic sites of small intestinal tissue remains challenging. In this study, hyperspectral imaging (HSI) and unsupervised classification techniques were used to distinguish normal and necrotic sites of small intestinal tissues. Small intestinal tissue hyperspectral images of eight Japanese large-eared white rabbits were acquired using a visible near-infrared hyperspectral camera, and K-means and density peaks (DP) clustering algorithms were used to differentiate between normal and necrotic tissue. The three cases in this study showed that the average clustering purity of the DP clustering algorithm reached 92.07% when the two band combinations of 500-622 and 700-858 nm were selected. The results of this study suggest that HSI and DP clustering can assist physicians in distinguishing between normal and necrotic sites in the small intestine in vivo.

Preparation and Microstructure of High-Activity Spherical TaNbTiZr Refractory High-Entropy Alloy Powders.

High-activity spherical TaNbTiZr refractory high-entropy alloy (REHA) powders were successfully prepared by electrode induction melting gas atomization (EIGA) and plasma rotating electrode process (PREP) methods. Both the EIGAed and PREPed TaNbTiZr RHEA powders have a single-phase body-centered cubic (BCC) structure and low oxygen content. Compared with the EIGAed powders, the PREPed powders exhibit higher sphericity and smoother surface, but larger particle size. The average particle sizes of the EIGAed and PREPed powders are 51.8 and 65.9 µm, respectively. In addition, both the coarse EIGAed and PREPed powders have dendritic structure, and the dendrite size of the EIGAed powders is larger than that of the PREPed powders. Theoretical calculation indicates that the cooling rate of the PREPed powders is one order of magnitude higher than that of the EIGAed powders during the solidification process, and the dendritic structure has more time to grow during EIGA, which is the main reason for the coarser dendrite size of the EIGAed powders.

Association between nonalcoholic fatty liver disease and increased glucose-to-albumin ratio in adults without diabetes.

Background: Nonalcoholic fatty liver disease (NAFLD) affects approximately 30% of individuals globally. Both serum glucose and albumin were demonstrated to be potential markers for the development of NAFLD. We hypothesized that the risk of NAFLD may be proportional to the glucose-to-albumin ratio (GAR). Methods: Based on information from the National Health and Nutrition Examination Survey (NHANES) 1999-2018, it was determined that GAR was associated with an increased risk of NAFLD and liver fibrosis utilizing weighted multivariable logistic regression. Participants with a fatty liver index (FLI) over 60 were identified with NAFLD, and those with an NAFLD fibrosis score (NFS) >0.676 with evidence of NAFLD were labeled with advanced hepatic fibrosis (AHF). The liver biopsy was utilized to verify the relationship between GAR and FLD in our center cohort. Mendelian randomization analysis investigated the genetic relationship between GAR and NAFLD. Results: Of 15,534 eligible participants, 36.4% of participants were identified as NAFLD without AHF. GAR was positively correlated with the probability of NAFLD following full adjustment for possible variables (OR = 1.53, 95% CI: 1.39-1.67). It was confirmed that patients with NAFLD and AHF had an inferior prognosis. The relationship between GAR and NFS was favorable (R = 0.46, P< 0.0001), and NAFLD patients with a higher GAR tended to develop poor survival. In our center cohort, the association between GAR and NAFLD was verified. Conclusion: Among participants without diabetes, greater GAR was linked to higher risks of NAFLD. In addition, NAFLD patients with higher GAR tended to develop liver fibrosis and adverse outcomes.

Visible near-infrared hyperspectral imaging and supervised classification for the detection of small intestinal necrosis tissue in vivo.

Complete recognition of necrotic areas during small bowel tissue resection remains challenging due to the lack of optimal intraoperative aid identification techniques. This research utilizes hyperspectral imaging techniques to automatically distinguish normal and necrotic areas of small intestinal tissue. Sample data were obtained from the animal model of small intestinal tissue of eight Japanese large-eared white rabbits developed by experienced physicians. A spectral library of normal and necrotic regions of small intestinal tissue was created and processed using six different supervised classification algorithms. The results show that hyperspectral imaging combined with supervised classification algorithms can be a suitable technique to automatically distinguish between normal and necrotic areas of small intestinal tissue. This new technique could aid physicians in objectively identify normal and necrotic areas of small intestinal tissue.

[Design and Realization of Personalized Corneal Analysis Software Based on Corneal Topography System].

As the most important refraction part in the optical system,cornea possesses characteristics which are important parameters in ophthalmology clinical surgery.During the measurement of the cornea in our study,we acquired the corneal data of Orbscan Ⅱ corneal topographer in real time using the Hook technology under Windows,and then took the data into the corneal analysis software.We then further analyzed and calculated the data to obtain individual Q-value of overall corneal 360semi-meridian.The corneal analysis software took Visual C++ 6.0as development environment,used OpenGL graphics technology to draw three-dimensional individual corneal morphological map and the distribution curve of the Q-value,and achieved real-time corneal data query.It could be concluded that the analysis would further extend the function of the corneal topography system,and provide a solid foundation for the further study of automatic screening of corneal diseases.

Three-dimensional model for human anterior corneal surface.

The anterior corneal asphericity (Q) with the tangential radius is calculated, and a three-dimensional (3-D) anterior corneal model is constructed. Tangential power maps from Orbscan II are acquired for 66 young adult subjects. The Q-value of each semimeridian in the near-horizontal region is calculated with the tangential radius. Polynomial fitting is used to model the 360-semimeridional variation of Q-values, and to fit the Q-values in the near-vertical region. Furthermore, a customized 3-D anterior corneal model is constructed. The 360-semimeridional variation of Q-values is well fitted with a seventh-degree polynomial function for all subjects. The goodness of fit of the polynomial function was >0.9, and the median value was 0.94. The Q-value distribution of the anterior corneal surface showed bimodal variation. Additionally, the Q-values gradually become less negative from the horizontal to the vertical semimeridians in the four quadrants. The 3-D surface plot of the anterior corneal surface approximated a prolate ellipsoid. Using a method to calculate the Q-value with the tangential radius combined with polynomial fitting, we are able to obtain the Q-value of any semimeridian. Compared with general models, this method generates a complete shape of the anterior corneal surface using asphericity.