Progress of Angiogenesis Signal Pathway and Antiangiogenic Drugs in Nasopharyngeal Carcinoma.

Nasopharyngeal cancer is a rare cancer with unique ethnic and geographic distribution. Since nasopharyngeal cancer often originates from the pharyngeal crypt, early symptoms are not obvious. They are difficult to detect in time, and the disease is usually diagnosed and treated only when it has progressed to an advanced-stage. Since angiogenesis is essential for the growth and invasion of solid tumors, antiangiogenic therapy has become a common treatment strategy for many solid tumors, and it has also achieved remarkable results in the treatment of nasopharyngeal carcinoma, which is prone to recurrence and distant metastasis. In this paper, we review the latest research progress of antiangiogenic drugs for nasopharyngeal carcinoma and their antiangiogenic mechanism of action and further propose some promising antiangiogenic therapeutic targets.

Ultralow-power optoelectronic synaptic transistors based on polyzwitterion dielectrics for in-sensor reservoir computing.

Bio-inspired transistor synapses use solid electrolytes to achieve low-power operation and rich synaptic behaviors via ion diffusion and trapping. While these neuromorphic devices hold great promise, they still suffer from challenges such as high leakage currents and power consumption, electrolysis risk, and irreversible conductance changes due to long-range ion migrations and permanent ion trapping. In addition, their response to light is generally limited because of "exciton-polaron quenching", which restricts their potential in in-sensor neuromorphic visions. To address these issues, we propose replacing solid electrolytes with polyzwitterions, where the cation and anion are covalently concatenated via a flexible alkyl chain, thus preventing long-range ion migrations while inducing good photoresponses to the transistors via interfacial charge trapping. Our detailed studies reveal that polyzwitterion-based transistors exhibit optoelectronic synaptic behavior with ultralow-power consumption (~250 aJ per spike) and enable high-performance in-sensor reservoir computing, achieving 95.56% accuracy in perceiving the trajectory of moving basketballs.

Induced ferromagnetism in Ni(II) doped ZnO monolayers via Al co-doping and their optical characteristics:ab initiostudy.

For applications in magneto-electronic devices, diluted magnetic semiconductors (DMSs) usually exhibit spin-dependent coupling and induced ferromagnetism at high Curie temperatures. The processes behind the behavior of optical emission and ferromagnetism, which can be identified by complicated microstructural and chemical characteristics, are still not well understood. In this study, the impact of Al co-doping on the electronic, optical, and magnetic properties of Ni(II) doped ZnO monolayers has been investigated using first principles calculations. Ferromagnetism in the co-doped monolayer is mainly triggered by the exchange coupling between the electrons provided by Al co-doping and Ni(II)-dstates; therefore, the estimated Curie temperature is greater than room temperature. The spin-spin couplings in mono-doped and co-doped monolayers were explained using the band-coupling mechanism. Based on the optical study, we observed that the Ni-related absorption peak occurred at 2.13-2.17 eV, showing a redshift as Ni concentrations increased. The FM coupling between Ni ions in the co-doped monolayer may be responsible for the reduction in the fundamental band gap seen with Al co-doping. We observed peaks in the near IR and visible regions of the co-doped monolayer, which improve the optoelectronic device's photovoltaic performance. Additionally, the correlation between optical characteristics and spin-spin couplings has been studied. We found that the Ni(II)'sd-dtransition bands or fundamental band gap in the near configuration undergoes a significant shift in response to AFM and FM coupling, whereas in the far configuration, they have a negligible shift due to the paramagnetic behavior of the Ni ions. These findings suggest that the magnetic coupling in DMS may be utilized for controlling the optical characteristics.

Multicolor Photochemical Printing Inside Polymer Matrices for Advanced Photonic Anticounterfeiting.

Conventional security inks, generally directly printed on the data page surface, are vulnerable to counterfeiters, thereby raising the risk of chemical structural deciphering. In fact, polymer film-based data pages with customized patterns embedded within polymer matrix, rather than printed on the surface, emerge as a promising solution. Therefore, the key lies in developing fluorophores offering light dose-controlled fluorescent color inside polymer matrices. Though conventional fluorophores often suffer from photobleaching and uncontrolled photoreactions, disqualifying them for this purpose. Herein a diphenanthridinylfumaronitrile-based phototransformers (trans-D5) that undergoes photoisomerization and subsequent photocyclization during photopolymerization of the precursor, successively producing cis- and cyclo-D5 with stepwise redshifted solid-state emissions is developed. The resulting cyclo-D5 exhibits up to 172 nm emission redshift in rigidifying polymer matrices, while trans-D5 experiences a slightly blueshifted emission (≈28 nm), cis-D5 undergoes a modest redshift (≈14 nm). The markedly different rigidochromic behaviors of three D5 molecules within polymer matrices enable multicolor photochemical printing with a broad hue ranging from 38 to 10 via an anticlockwise direction in Munsell color space, yielding indecipherable fluorescent patterns in polymer films. This work provides a new method for document protection and implements advanced security features that are unattainable with conventional inks.

One-Dimensional Covalent Organic Framework-Based Multilevel Memristors for Neuromorphic Computing.

Memristors are essential components of neuromorphic systems that mimic the synaptic plasticity observed in biological neurons. In this study, a novel approach employing one-dimensional covalent organic framework (1D COF) films was explored to enhance the performance of memristors. The unique structural and electronic properties of two 1D COF films (COF-4,4'-methylenedianiline (MDA) and COF-4,4'-oxydianiline (ODA)) offer advantages for multilevel resistive switching, which is a key feature in neuromorphic computing applications. By further introducing a TiO2 layer on the COF-ODA film, a built-in electric field between the COF-TiO2 interfaces could be generated, demonstrating the feasibility of utilizing COFs as a platform for constructing memristors with tunable resistive states. The 1D nanochannels of these COF structures contributed to the efficient modulation of electrical conductance, enabling precise control over synaptic weights in neuromorphic circuits. This study also investigated the potential of these COF-based memristors to achieve energy-efficient and high-density memory devices.

Renal-clearable nanoprobes for optical imaging and early diagnosis of diseases.

Optical imaging has played an indispensable role in clinical diagnostics and fundamental biomedical research due to its high sensitivity, high spatiotemporal resolution, cost-effectiveness, and easy accessibility. However, the issues of light scattering and low tissue penetration make them effective only for superficial imaging. To overcome these issues, renal-clearable optical nanoprobes have recently emerged, which are activated by abnormal disease-associated biomarkers and initiate a pharmacokinetic switch by undergoing degradation and eventually releasing signal reporters into urine, for simple imaging and sensitive optical in vitro urinalysis. In this review, we focus on the advancements of renal-clearable organic nanoprobes for optical imaging and remote urinalysis. The versatile design strategies of these nanoprobes are discussed along with their sensing mechanisms toward biomolecules of interest as well as their unique biological applications. Finally, challenges and perspectives are discussed to further advance the next-generation renal-clearable nanoprobes for in vivo imaging and in vitro urinalysis.

Realizing efficient broadband near-infrared emission and multimode photoluminescence switching via coordination structure modulation in Sb3+-doped 0D organic metal chlorides.

Recently, organic Sb(III)-based metal halides have achieved significant results in the visible light region due to their efficient emission. However, realizing efficient broadband near-infrared (NIR) emission in such materials is a great challenge. Herein, we developed three different NIR emitters via a coordination structure modulation strategy in Sb3+-doped zero-dimensional organic metal chlorides of (C20H20P)2MnCl4, (C20H20P)2ZnCl4, and (C20H20P)2CdCl4 with tetrahedral structure. More specifically, after the dopant Sb3+ is inserted into the host lattice, the coordination structures of Sb3+ ions can change from [SbCl5]2- square-pyramidal configuration to [SbCl4]- clusters, which will bring a larger lattice distortion degree to the excited state compared to the ground state, resulting in a larger Stokes shift. Thus, efficient NIR emission with near-unity photoluminescence quantum yield (PLQY) can be obtained in Sb3+-doped compounds under 365 nm excitation. Moreover, Sb3+-doped NIR emitters also show remarkable stabilities, which prompts us to fabricate NIR phosphor conversion light-emitting diodes (pc-LEDs) and demonstrate their application in night vision. More interestingly, the Sb3+-doped (C20H20P)2MnCl4 shows tunable emission characteristics, which can be tuned from green to greenish-yellow, orange, red, and NIR emission under different external stimuli, and thus we can demonstrate the applications of this compound in quintuple-mode fluorescence anti-counterfeiting and information encryption.

In Situ Optical Detection of Amines at a Parts-per-Quadrillion Level by Severing the Through-Space Conjugated Supramolecular Domino.

Conventional fluorophores suffer from low sensitivity and selectivity in amine detection due to the inherent limitations in their "one-to-one" stoichiometric sensing mechanism. Herein, we propose a "one-to-many" chain reaction-like sensing mechanism by creating a domino chain consisting of one fluorescent molecule (e.g., PTF1) and up to 40 nonemissive polymer chains (pPFPA) comprising over thousand repeating units (PFPA). PTF1 (the domino trigger) interacts with adjacent PFPA units (the following blocks) through polar-π interactions and initiates the domino effect, creating effective through-space conjugation along pPFPA chains and generating amplified yellow fluorescent signals through charge transfer between PTF1 and pPFPA. Amine exposure causes rapid dismantling of the fluorophore-pPFPA-based domino chain and significantly reduces the amplified emissions, thus providing an ultrasensitive method for detecting amines. Relying on the above merits, we achieve a limit of detection of 177 ppq (or 1.67 × 10-12 M) for triethylamine, which is nearly 4 orders lower than that of previous methods. Additionally, the distinct reactivity of pPFPA toward different amines allows for the discrimination of primary, secondary, and tertiary amines. This study presents a "domino effect" sensing mechanism that has not yet been reported and provides a general approach for chemical detection that is beyond the reach of conventional methods.

Breaking the Trade-Off Between Polymer Dielectric Constant and Loss via Aluminum Oxo Macrocycle Dopants for High-Performance Neuromorphic Electronics.

The dielectric layer is crucial in regulating the overall performance of field-effect transistors (FETs), the key component in central processing units, sensors, and displays. Despite considerable efforts being devoted to developing high-permittivity (k) dielectrics, limited progress is made due to the inherent trade-off between dielectric constant and loss. Here, a solution is presented by designing a monodispersed disk-shaped Ce-Al-O-macrocycle as a dopant in polymer dielectrics. The molecule features a central Ce(III) core connected with eight Al atoms through sixteen bridging hydroxyls and eight 3-aminophenyl peripheries. The incorporation of this macrocycle in polymer dielectrics results in an up to sevenfold increase in dielectric constants and up to 89% reduction in dielectric loss at low frequencies. Moreover, the leakage-current densities decrease, and the breakdown strengths are improved by 63%. Relying on the above merits, FETs bearing cluster-doped polymer dielectrics give near three-orders source-drain current increments while maintaining low-level leakage/off currents, resulting in much higher charge-carrier mobilities (up to 2.45 cm2  V-1  s-1 ) and on/off ratios. This cluster-doping strategy is generalizable and shows great promise for ultralow-power photoelectric synapses and neuromorphic retinas. This work successfully breaks the trade-off between dielectric constant and loss and offers a unique design for polymer composite dielectrics.

Morphological component analysis under non-convex smoothing penalty framework for gearbox fault diagnosis.

The sparse representation methodology has been identified to be a promising tool for gearbox fault diagnosis. The core is how to precisely reconstruct the fault signal from noisy monitoring signals. The non-convex penalty has the ability to induce sparsity more efficiently than convex penalty. However, the introduction of non-convex penalty usually influences the convexity of the model, resulting in the unstable or sub-optimal solution. In this paper, we propose the non-convex smoothing penalty framework (NSPF) and combine it with morphological component analysis (MCA) for gearbox fault diagnosis. The proposed NSPF is a unify penalty construction framework, which contains many classical penalty while a new set of non-convex smoothing penalty functions can be generated. These non-convex penalty can guarantee the convexity of the objective function while enhancing the sparsity, thus the global optimal solution can be acquired. The simulation and engineering experiments validate that the NSPF enjoys more reconstruction precision compared to the existing penalties.

[Effectiveness analysis of posterolateral approach lumbar interbody fusion assisted by one-hole split endoscope for L4, 5 degenerative lumbar spondylolisthesis].

Objective: To compare the effectiveness of posterolateral approach lumbar interbody fusion assisted by one-hole split endoscope (OSE) and traditional posterior lumbar interbody fusion (PLIF) in the treatment of L4, 5 degenerative lumbar spondylolisthesis (DLS). Methods: The clinical data of 58 patients with DLS who met the selection criteria admitted between February 2020 and March 2022 were retrospectively analyzed, of which 26 were treated with OSE-assisted posterolateral approach lumbar interbody fusion (OSE group) and 32 were treated with PLIF (PLIF group). There was no significant difference between the two groups in terms of gender, age, body mass index, Meyerding grade, lower limb symptom side, decompression side, stenosis type, and preoperative low back pain visual analogue scale (VAS) score, leg pain VAS score, Oswestry disability index (ODI), and the height of the anterior and posterior margins of the intervertebral space (P>0.05). The operation time, intraoperative blood loss, postoperative hospital stay, and complications were compared between the two groups. The low back pain and leg pain VAS scores and ODI before operation, at 1 month, 6 months after operation, and last follow-up, the height of anterior and posterior margins of the intervertebral space before operation, at 6 months after operation, and last follow-up, the modified MacNab criteria at last follow-up after operation were used to evaluate the effectiveness; and the Bridwell method at last follow-up was used to evaluate the interbody fusion. Results: Both groups successfully completed the operation. Compared with the PLIF group, the OSE group showed a decrease in intraoperative blood loss and postoperative hospital stay, but an increase in operation time, with significant differences (P<0.05). In the OSE group, no complication such as nerve root injury and thecal sac tear occurred; in the PLIF group, there were 1 case of thecal sac tear and 1 case of epidural hematoma, which were cured after conservative management. Both groups of patients were followed up 13-20 months with an average of 15.5 months. There was no complication such as loosening, sinking, or displacement of the fusion cage. The low back pain and leg pain VAS scores, ODI, and the height of anterior and posterior margins of the intervertebral space at each time point after operation in both groups were significantly improved when compared with those before operation (P<0.05). Except for the VAS score of lower back pain in the OSE group being significantly better than that in the PLIF group at 1 month after operation (P<0.05), there was no significant difference in all indicators between the two groups at all other time points (P>0.05). At last follow-up, both groups achieved bone fusion, and there was no significant difference in Bridwell interbody fusion and modified MacNab standard evaluation between the two groups (P>0.05). Conclusion: OSE-assisted posterolateral approach lumbar interbody fusion for L4, 5 DLS, although the operation time is relatively long, but the postoperative hospitalization stay is short, the complications are few, the operation is safe and effective, and the early effectiveness is satisfactory.

Novel risk model based on angiogenesis-related lncRNAs for prognosis prediction of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death due to early metastasis or recurrence. Tumor angiogenesis plays an essential role in the tumorigenesis of HCC. Accumulated studies have validated the crucial role of lncRNAs in tumor angiogenesis. Here, we established an angiogenesis-related multi-lncRNAs risk model based on the machine learning for HCC prognosis prediction. Firstly, a total of 348 differential expression angiogenesis-related lncRNAs were identified by correlation analysis. Then, 20 of these lncRNAs were selected through univariate cox analysis and used for in-depth study of machine learning. After 1,000 random sampling cycles calculating by random forest algorithm, four lncRNAs were found to be highly associated with HCC prognosis, namely LUCAT1, AC010761.1, AC006504.7 and MIR210HG. Subsequently, the results from both the training and validation sets revealed that the four lncRNAs-based risk model was suitable for predicting HCC recurrence. Moreover, the infiltration of macrophages and CD8 T cells were shown to be closely associated with risk score and promotion of immune escape. The reliability of this model was validated by exploring the biological functions of lncRNA MIR210HG in HCC cells. The results showed that MIR210HG silence inhibited HCC growth and migration through upregulating PFKFB4 and SPAG4. Taken together, this angiogenesis-related risk model could serve as a reliable and promising tool to predict the prognosis of HCC.

Conventional Non-Fluorescent Polymers: Unconventional Security Inks for Data Storage and Multidimensional Photonic Cryptography.

Traditional security inks relying on fluorescent/phosphorescent molecules are facing increasing risks of forgery or tampering due to their simple readout scheme (i.e., UV-light irradiation) and the advancement of counterfeiting technologies. In this work, a multidimensional data-encryption method based on non-fluorescent polymers via a "lock-key" mechanism is developed. The non-fluorescent invisible polymer inks serve as the "lock" for data-encryption, while the anti-rigidochromic fluorophores that can distinctively light up the polymer inks with programed emissions are "keys" for decryption. The emission of decrypted data is prescribed by polymer chemical structure, molecular weight, topology, copolymer sequence, and phase structure, and shows distinct intensity, wavelength, and chirality compared with the intrinsic emission of fluorophores. Therefore, the data is triply encrypted and naturally gains a high-security level, e.g., only one out of 20 000 keys can access the only correct readout from 40 000 000 possible outputs in a three-polymers-based data-encryption matrix. Note that fluorophores lacking anti-rigidochrimism cannot selectively light up the inks and fail in data-decryption. Further, the diverse topologies, less well-defined structures, and random-coiled shapes of polymers make it impossible for them to be imitated. This work offers a new design for security inks and boosts data security levels beyond the reach of conventional fluorescent inks.

NIR-II light evokes DNA cross-linking for chemotherapy and immunogenic cell death.

As a DNA damaging agent, oxaliplatin (OXA) can induce immunogenic cell death (ICD) in tumors to activate the immune system. However, the DNA damage induced by OXA is limited and the ICD effect is not strong enough to enhance anti-tumor efficacy. Here, we propose a strategy to maximize the ICD effect of OXA through the mild hyperthermia generated by nanoparticles with a platinum (IV) prodrug of OXA (Pt(IV)-C16) and a near-infrared-II (NIR-II) photothermal agent IR1061 upon the irradiation of NIR-II light. The mild hyperthermia (43 °C) holds advantages in two aspects: 1) increase the Pt-DNA cross-linking, leading to enhanced DNA damage and apoptosis; 2) induce stronger ICD effects for cancer immunotherapy. We demonstrated that, compared with OXA and photothermal therapy of IR1061 alone, these nanoparticles under NIR-II light irradiation can significantly improve the anti-cancer efficacy against triple-negative breast cancer 4T1 tumor. This new strategy provides an effective way to improve the therapeutic outcome of OXA. STATEMENT OF SIGNIFICANCE: OXA could induce immunogenic cell death (ICD) via stimulating immune responses by increasing tumor cell stress and death, which triggers tumor-specific immune responses to achieve immunotherapy. However, due to the insufficient Pt-DNA crosslinks, the ICD effect triggered by OXA cannot induce robust immune response. Mild hyperthermia has great potential to maximize the therapeutic outcome of oxaliplatin by increasing the Pt-DNA cross-linking to augment the immunoresponse for enhanced cancer immunotherapy.

Wearable in-sensor reservoir computing using optoelectronic polymers with through-space charge-transport characteristics for multi-task learning.

In-sensor multi-task learning is not only the key merit of biological visions but also a primary goal of artificial-general-intelligence. However, traditional silicon-vision-chips suffer from large time/energy overheads. Further, training conventional deep-learning models is neither scalable nor affordable on edge-devices. Here, a material-algorithm co-design is proposed to emulate human retina and the affordable learning paradigm. Relying on a bottle-brush-shaped semiconducting p-NDI with efficient exciton-dissociations and through-space charge-transport characteristics, a wearable transistor-based dynamic in-sensor Reservoir-Computing system manifesting excellent separability, fading memory, and echo state property on different tasks is developed. Paired with a 'readout function' on memristive organic diodes, the RC recognizes handwritten letters and numbers, and classifies diverse costumes with accuracies of 98.04%, 88.18%, and 91.76%, respectively (higher than all reported organic semiconductors). In addition to 2D images, the spatiotemporal dynamics of RC naturally extract features of event-based videos, classifying 3 types of hand gestures at an accuracy of 98.62%. Further, the computing cost is significantly lower than that of the conventional artificial-neural-networks. This work provides a promising material-algorithm co-design for affordable and highly efficient photonic neuromorphic systems.

Configuration-Induced Multichromism of Phenanthridine Derivatives: A Type of Versatile Fluorescent Probe for Microenvironmental Monitoring.

Fluorescent probes are attractive in diagnosis and sensing. However, most reported fluorophores can only detect one or few analytes/parameters, notably limiting their applications. Here we have designed three phenanthridine-based fluorophores (i.e., B1, F1, and T1 with 1D, 2D, and 3D molecular configuration, respectively) capable of monitoring various microenvironments. In rigidifying media, all fluorophores show bathochromic emissions but with different wavelength and intensity changes. Under compression, F1 shows a bathochromic emission of over 163 nm, which results in organic fluorophore-based full-color piezochromism. Moreover, both B1 and F1 exhibit an aggregation-caused quenching (ACQ) behavior, while T1 is an aggregation-induced emission (AIE) fluorophore. Further, F1 and T1 selectively concentrate in cell nucleus, whereas B1 mainly stains the cytoplasm in live cell imaging. This work provides a general design strategy of versatile fluorophores for microenvironmental monitoring.

Harnessing molecular isomerization in polymer gels for sequential logic encryption and anticounterfeiting.

Using smart photochromic and luminescent tissues in camouflage/cloaking of natural creatures has inspired efforts to develop synthetic stimuli-responsive materials for data encryption and anticounterfeiting. Although many optical data-encryption materials have been reported, they generally require only one or a simple combination of few stimuli for decryptions and rarely offer output corruptibility that prevents trial-and-error attacks. Here, we report a series of multiresponsive donor-acceptor Stenhouse adducts (DASAs) with unprecedented switching behavior and controlled reversibility via diamine conformational locking and substrate free-volume engineering and their capability of sequential logic encryption (SLE). Being analogous to the digital circuits, the output of DASA gel-based data-encryption system depends not only on the present input stimulus but also on the sequence of past inputs. Incorrect inputs/sequences generate substantial fake information and lead attackers to the point of no return. This work offers new design concepts for advanced data-encryption materials that operate via SLE, paving the path toward advanced encryptions beyond digital circuit approaches.

Data storage and encryption with a high security level based on molecular configurational isomers.

Developing advanced materials for highly secure data-encryption is crucial but very challenging, as most data-encryption materials (the message area) are chemically different from the substrates (the background) on which they are being written, leading to high risks of data leakage by deciphering via sophisticated instrumental analysis. Additionally, most materials require only one stimulus for decryption, resulting in a low-level of data-security. Here, a three configurational isomer-based data-encryption method is developed (i.e., propylamine, isopropylamine, and cyclopropylamine). Their similar molecular formulae, elemental constitution, and physiochemical properties make them ideal date-encryption materials. On the other hand, the significant differences in lower critical solution temperatures (LCST) of the corresponding polyacrylamides, i.e., 10 °C for poly(N-propylacrylamide), 32 °C for poly(N-isopropylacrylamide), and 53 °C for poly(N-cyclopropylacrylamide), respectively, render an effective method for data decryption. Relying on the above features, the data written by three isomers are well-hidden under given conditions. And a specific temperature range, rather than a simple temperature increase or decrease, would be required for decryption. Furthermore, undesired temperatures give wrong outputs, which is highly deceptive to the hacker. Therefore, a high-level of data security can be achieved. This result opens a new door for designing advanced materials for improving the data-security level.

Piperine alleviates acute pancreatitis: A possible role for FAM134B and CCPG1 dependent ER-phagy.

BACKGROUND: Acute pancreatitis was a common acute abdominal disease characterized by pancreatic acinar cell death and inflammation. Endoplasmic reticulum autophagy (ER-phagy) coud maintain cell homeostasis by degrading redundant and disordered endoplasmic reticulum and FAM134B and CCPG1 was main ER-phagy receptors. As a natural alkaloid, piperin is found in black pepper and has anti-inflammatory properties, whose effect on ER-phagy in pancreatitis has not been studied. PURPOSE: The objective of this study was to demonstrate the pivotal role of FAM134B and CCPG1 dependent ER-phagy for alleviating acute pancreatitis and explore the molecular mechanism of piperine in alleviating acute pancreatitis. METHOD: In this study we investigated the role of ER-phagy in acute pancreatitis and whether piperine could alleviate pancreatitis through ER-phagy regulation. We first detected endoplasmic reticulum stress (ER-stress) and ER-phagy in different degrees of acute pancreatitis. Then we used ER-stress and autophagy regulators to explore the relationship between ER-stress and ER-phagy in acute pancreatitis and their regulation of cell death. Through using FAM134B-/- and CCPG1-/-, we investigated the mechanism of piperine in the treatment of acute pancreatitis. RESULTS: In this study, we confirmed that with the progression of acute pancreatitis, the pancreatic endoplasmic reticulum stress increased continuously, but the ER-phagy increased first and then was inhibited. Meanwhile, in acute pancreatitis, ER-stress and ER-phagy interacted: endoplasmic reticulum stress can induce ER-phagy, but serious ER-stress would inhibit ER-phagy; and ER-phagy could alleviate ER-stress. Next, we found that piperine reduced ER-stress by enhancing FAM134B and CCPG1 dependent ER-phagy, thereby alleviating pancreatic injury. CONCLUSION: Impaired ER-phagy was both a cause and a consequence of ER-stress in AP mice, which contributed to the transition from AP to SAP. Piperine targeting ER-phagy provided a new insight into the pharmacological mechanism of piperine in treating AP.

Novel Prognostic Signatures of Hepatocellular Carcinoma Based on Metabolic Pathway Phenotypes.

Hepatocellular carcinoma is a disastrous cancer with an aberrant metabolism. In this study, we aimed to assess the role of metabolism in the prognosis of hepatocellular carcinoma. Ten metabolism-related pathways were identified to classify the hepatocellular carcinoma into two clusters: Metabolism_H and Metabolism_L. Compared with Metabolism_L, patients in Metabolism_H had lower survival rates with more mutated TP53 genes and more immune infiltration. Moreover, risk scores for predicting overall survival based on eleven differentially expressed metabolic genes were developed by the least absolute shrinkage and selection operator (LASSO)-Cox regression model in The Cancer Genome Atlas (TCGA) dataset, which was validated in the International Cancer Genome Consortium (ICGC) dataset. The immunohistochemistry staining of liver cancer patient specimens also identified that the 11 genes were associated with the prognosis of liver cancer patients. Multivariate Cox regression analyses indicated that the differentially expressed metabolic gene-based risk score was also an independent prognostic factor for overall survival. Furthermore, the risk score (AUC = 0.767) outperformed other clinical variables in predicting overall survival. Therefore, the metabolism-related survival-predictor model may predict overall survival excellently for HCC patients.