[Establishment of a prostate cancer prognostic risk model based on the TCGA database and inflammation-related genes].

OBJECTIVE: To investigate the effect of inflammation-related genes on the prognosis of prostate cancer (PCa). METHODS: We downloaded PCa-related clinical data and mRNA sequencing data from the database Cancer Genome Atlas (TCGA) and inflammation-related pathway gene sets from MsigDB. Using univariate regression and LASSO regression analyses, we screened inflammation-related genes for the construction of a prognostic risk model and evaluated the performance of the model in predicting the prognosis of PCa by Kaplan-Meier and ROC analyses. Based on the nomogram, we calculated the risk scores of the patients, divided them into a high-risk and a low-risk group based on the median values of their risk scores, identified differentially expressed genes for enrichment analysis and verified the expression level of SPHK1 in the PCa tissue microarrays by immunohistochemical staining. RESULTS: Totally 19 inflammation-related genes were identified from 172 candidate genes for the construction of the prognostic risk model, including the risk genes CD14, PIK3R5, GABBR1, RELA, IRF7, SCARF1, MSR1, SPHK1, OSM and STAB1, and the protective genes AQP9, LPAR1, ATP2C1, NDP, CXCL6, P2RY2, DCBLD2, PCDH7, and IFNAR1. Kaplan-Meier analysis showed that the patients with high risk scores had a significantly lower recurrence-free survival and a worse prognosis than those with low risk scores. Differentially expressed genes were involved mainly in the activation of inflammatory response pathways. Immunohistochemical results indicated that the expression of SPHK1 was significantly higher in the tumorous than in the normal tissue and increased with the Gleason score. There was a correlation between the SPHK1 expression and envelope invasion. CONCLUSION: The prognostic risk model of inflammation-related genes constructed based on the TCGA database can effectively predict the prognosis of PCa.

[Omics molecular subtyping, prognostic prediction and individualized treatment of prostate cancer: Advances in studies].

Prostate cancer (PCa) is a most common malignancy in males. It has a greater heterogeneity than other cancers, which poses a real challenge to the clinical diagnosis, classification and prognostic monitoring. At present, high-, medium- and low-risk PCa patients are classified mainly by Gleason scores and the PSA level, which, however, fail to reveal the diverse molecular heterogeneity and precisely distinguish the molecular subtypes of PCa. With the development of high-throughput sequencing, more and more studies on the molecular classification of the malignancy have paved the theoretical ground for the early diagnosis, efficacy prediction and individualized treatment of PCa. This study reviews the molecular classification, prognosis prediction and individualized treatment of PCa to date, hoping to contribute to the development of the precise treatment of PCa.

Flexible boron nitride-based memristor for in situ digital and analogue neuromorphic computing applications.

The data processing efficiency of traditional computers is suffering from the intrinsic limitation of physically separated processing and memory units. Logic-in-memory and brain-inspired neuromorphic computing are promising in-memory computing paradigms for improving the computing efficiency and avoiding high power consumption caused by extra data movement. However, memristors that can conduct digital memcomputing and neuromorphic computing simultaneously are limited by the difference in the information form between digital data and analogue data. In order to solve this problem, this paper proposes a flexible low-dimensional memristor based on boron nitride (BN), which has ultralow-power non-volatile memory characteristic, reliable digital memcomputing capabilities, and integrated ultrafast neuromorphic computing capabilities in a single in situ computing system. The logic-in-memory basis, including FALSE, material implication (IMP), and NAND, are implemented successfully. The power consumption of the proposed memristor per synaptic event (198 fJ) can be as low as biology (fJ level) and the response time (1 µs) of the neuromorphic computing is four orders of magnitude shorter than that of the human brain (10 ms), paving the way for wearable ultrahigh efficient next-generation in-memory computing architectures.

CMOS back-end compatible memristors for in situ digital and neuromorphic computing applications.

In-memory logic calculations and brain-inspired artificial synaptic neuromorphic computing are expected to solve the limitations of the traditional von Neumann computing architecture. The data processing efficiency of the traditional von Neumann architecture is inherently limited by its physically separated processing and storage units, and thus data transmission besides calculation leads to a limited calculation speed and additional high-power consumption. In addition, traditional digital logic calculations and analog calculations have greater limitations in conversion. Herein, we report a flexible two-terminal memristor based on SiCO:H, which is a porous low-k back-end complementary metal-oxide-semiconductor (CMOS)-compatible material. Due to its low operating voltage (200 mV) and fast response speed (100 ns), it could perform digital memory calculation and neuromorphic calculation simultaneously. The memristor could realize a transition from short-term to long-term plasticity in the process of enhancement and inhibition during neuromorphic calculation, with high biological reality. In digital logic calculations, IMP-based and MAGIC-based logic calculations were verified. In neuromorphic computing, an Ag ion-based conductive filament was introduced. The relationship between the temporal dynamics of the conductance evolution and the diffusive dynamics of the Ag active metal could be modulated by the external programming electric field strength. The synapses and neuron dynamics in biology were faithfully simulated, realizing a transition from short-term to long-term plasticity in the process of enhancement and inhibition, which has high compatibility and scalability, proposing a novel solution for the next generation of computer architectures.

Neo-adjuvant radiation therapy provides a survival advantage in T3-T4 nodal positive gastric and gastroesophageal junction adenocarcinoma: a SEER database analysis.

BACKGROUND: Due to negative results in clinical trials of postoperative chemoradiation for gastric cancer, at present, there is a tendency to move chemoradiation therapy forward in gastric and gastroesophageal junction (GEJ) adenocarcinoma. Several randomized controlled trials (RCTs) are currently recruiting subjects to investigate the effect of neo-adjuvant radiotherapy (NRT) in gastric and GEJ cancer. Large retrospective studies may be beneficial in clarifying the potential benefit of NRT, providing implications for RCTs. METHODS: We retrieved the clinicopathological and treatment data of gastric and GEJ adenocarcinoma patients who underwent surgical resection and chemotherapy between 2004 and 2015 from Surveillance, Epidemiology, and End Results (SEER) database. We compared survival between NRT and non-NRT patients among four clinical subgroups (T1-2N-, T1-2N+, T3-4N-, and T3-4N+). RESULTS: Overall, 5272 patients were identified, among which 1984 patients received NRT. After adjusting confounding variables, significantly improved survival between patients with and without NRT was only observed in T3-4N+ subgroup [hazard ratio (HR) 0.79, 95% confidence interval (CI): 0.66-0.95; P = 0.01]. Besides, Kaplan-Meier plots showed significant cause-specific survival advantage of NRT in intestinal type (P <  0.001), but not in diffuse type (P = 0.11) for T3-4N+ patients. In the multivariate competing risk model, NRT still showed survival advantage only in T3-4 N+ patients (subdistribution HR: 0.77; 95% CI: 0.64-0.93; P = 0.006), but not in other subgroups. CONCLUSIONS: NRT might benefit resectable gastric and GEJ cancer patients of T3-4 stages with positive lymph nodes, particularly for intestinal-type. Nevertheless, these results should be interpreted with caution, and more data from ongoing RCTs are warranted.

Specific epigenetic age acceleration patterns among four molecular subtypes of gastric cancer and their prognostic value.

Aims: To determine the association of the methylation age (Horvath epigenetic clock) of gastric cancer (GC) tissues with molecular subtypes and patient survival. Materials & methods: Multivariate regression models were used to determine the association of methylation age acceleration (AA) with the clinical and molecular characteristics of 333 GC patients. Results: Relative to the chromosomal instability subtype, the epigenetic AA was 49.8 (95% CI: 42.7-56.9) years for Epstein-Barr virus, 16.1 (10.6-21.6) years for microsatellite instability, and 6.05 (0.1-11.1) years for genomic stability subtype. GC patients with accelerated aging of tumor tissues had better outcomes (adjusted hazard ratio: 3.13; p = 0.03). Differentially methylated probes in patients with accelerated and decelerated methylation aging enriched in pathways including BMP signaling, HMGB1 signaling, STAT3 signaling and human embryonic stem cell pluripotency. Conclusions: Our results highlight the prognostic value of epigenetic AA in GC and suggest that epigenetic AA is also an indicator of molecular subtype in GC.

Qualitative Transcriptional Signature for the Pathological Diagnosis of Pancreatic Cancer.

It is currently difficult for pathologists to diagnose pancreatic cancer (PC) using biopsy specimens because samples may have been from an incorrect site or contain an insufficient amount of tissue. Thus, there is a need to develop a platform-independent molecular classifier that accurately distinguishes benign pancreatic lesions from PC. Here, we developed a robust qualitative messenger RNA signature based on within-sample relative expression orderings (REOs) of genes to discriminate both PC tissues and cancer-adjacent normal tissues from non-PC pancreatitis and healthy pancreatic tissues. A signature comprising 12 gene pairs and 17 genes was built in the training datasets and validated in microarray and RNA-sequencing datasets from biopsy samples and surgically resected samples. Analysis of 1,007 PC tissues and 257 non-tumor samples from nine databases indicated that the geometric mean of sensitivity and specificity was 96.7%, and the area under receiver operating characteristic curve was 0.978 (95% confidence interval, 0.947-0.994). For 20 specimens obtained from endoscopic biopsy, the signature had a diagnostic accuracy of 100%. The REO-based signature described here can aid in the molecular diagnosis of PC and may facilitate objective differentiation between benign and malignant pancreatic lesions.

[Effects of nitrogen fertilizer reduction and biochar application on paddy soil nutrient and nitrogen uptake of rice]. / å‡æ°®é æ–½ç¨»ç§†ç”Ÿç‰©ç‚­å¯¹ç¨»ç”°åœŸå£¤å »åˆ†åŠæ¤æ ªæ°®ç´ å¸æ”¶çš„å½±å“.

We explored the impacts of nitrogen (N) reduction and biochar application on soil fertility and nutrient uptake of rice in early and late seasons of 2018 with a field experiment. There were six treatments, including control (no N application, CK), conventional N application (N100), 20% N reduction (N80), 20% N reduction plus biochar application (N80+BC), 40% N reduction (N60), 40% N reduction plus biochar application (N60+BC). Our results showed that 20% and 40% N reduction and/or with biochar application did not affect soil pH, organic matter, total N, total phosphorous (P), total potassium (K), ammonium N, available P and K in comparison with N100 treatment. N80+BC and N60+BC substantially increased soil cation exchange capacity (CEC) at tillering stage and electrical conductivity (EC) at heading stage in late season, respectively. Compared with the treatment with single N reduction, N80+BC significantly increased soil available K in early and late seasons and soil pH and total N in late season, while N60+BC increased soil total K at mature stage in early season. Soil nitrate content was decreased along with the growth stages for all treatments in early season. Compared with tillering stage, soil nitrate N content in conventional N application at heading stage and mature stage was decreased by 50.0% and 71.6%, respectively. Soil nitrate content in biochar treatment only was decreased by 6.3%-45.5%. N application along with biochar application had no significant effects on plant N uptake and utilization in early season. However, N reduction with biochar application significantly increased plant N uptake and N utilization rate by 34.8%-52.4% in late season, compared to conventional N application and single N reduction. Our findings suggest that adequate N reduction along with biochar application could maintain soil health and improve plant N uptake and utilization efficiency.

Ultralow Power Wearable Heterosynapse with Photoelectric Synergistic Modulation.

Although the energy consumption of reported neuromorphic computing devices inspired by biological systems has become lower than traditional memory, it still remains greater than bio-synapses (≈10 fJ per spike). Herein, a flexible MoS2-based heterosynapse is designed with two modulation modes, an electronic mode and a photoexcited mode. A one-step mechanical exfoliation method on flexible substrate and low-temperature atomic layer deposition process compatible with flexible electronics are developed for fabricating wearable heterosynapses. With a pre-spike of 100 ns, the synaptic device exhibits ultralow energy consumption of 18.3 aJ per spike in long-term potentiation and 28.9 aJ per spike in long-term depression. The ultrafast speed and ultralow power consumption provide a path for a neuromorphic computing system owning more excellent processing ability than the human brain. By adding optical modulation, a modulatory synapse is constructed to dynamically control correlations between pre- and post-synapses and realize complex global neuromodulations. The novel wearable heterosynapse expands the accessible range of synaptic weights (ratio of facilitation ≈228%), providing an insight into the application of wearable 2D highly efficient neuromorphic computing architectures.

Room-temperature developed flexible biomemristor with ultralow switching voltage for array learning.

As one of the emerging neuromorphic computing devices, memristors may break through the limitation of traditional computers with a von Neumann architecture. However, the development of flexible memristors is limited by the high-temperature fabrication process, large operating voltage and non-uniform distribution of resistance. The room-temperature process has attracted great attention due to its advantages of low thermal dissipation, low cost and excellent compatibility with flexible electronics. Here, we proposed a fully physical vapour deposition (PVD) process for fabricating a memristor without additional heat treatment. The device showed excellent resistive switching characteristics with ultralow set/reset voltages (0.48 V/-0.39 V), uniform distribution (10%/15%), stable retention characteristic, multilevel storage behavior and reliable flexibility (radius of 10 mm). With continuously modulated conductance, typical synaptic plasticities were simulated by our flexible biomemristor, including excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), long-term potentiation/depression (LTP/LTD) and learning-forgetting curve. Furthermore, the array learning behavior like that of the human brain was simulated with these trainable biomemristors. This study paves a new way for developing low-cost, wearable, neuromorphic computing electronics at room temperature and expands the applications of artificial synapse arrays.

Three-Dimensional Nanoscale Flexible Memristor Networks with Ultralow Power for Information Transmission and Processing Application.

To construct an artificial intelligence system with high efficient information integration and computing capability like the human brain, it is necessary to realize the biological neurotransmission and information processing in artificial neural network (ANN), rather than a single electronic synapse as most reports. Because the power consumption of single synaptic event is ∼10 fJ in biology, designing an intelligent memristors-based 3D ANN with energy consumption lower than femtojoule-level (e.g., attojoule-level) and faster operating speed than millisecond-level makes it possible for constructing a higher energy efficient and higher speed computing system than the human brain. In this paper, a flexible 3D crossbar memristor array is presented, exhibiting the multilevel information transmission functionality with the power consumption of 4.28 aJ and the response speed of 50 ns per synaptic event. This work is a significant step toward the development of an ultrahigh efficient and ultrahigh-speed wearable 3D neuromorphic computing system.

MnFe2O4 nanoparticles accelerate the clearance of mutant huntingtin selectively through ubiquitin-proteasome system.

Neurodegenerative disorders such as Huntington's disease (HD) are fundamentally caused by accumulation of misfolded aggregate-prone proteins. Previous investigations have shown that these toxic protein aggregates could be degraded through autophagy induced by small molecules as well as by nanomaterials. However, whether engineered nanomaterials have the capacity to degrade these protein aggregates via the ubiquitin-proteasome system (UPS), the other major pathway for intracellular protein turnover, was unknown. Herein, we have synthesized biocompatible MnFe2O4 nanoparticles (NPs) and demonstrated their unique effect in accelerating the clearance of mutant huntingtin (Htt) protein exhibiting 74 glutamine repeats [Htt(Q74)]. UPS, rather than autophagy, was responsible for the efficient Htt(Q74) degradation facilitated by MnFe2O4 NPs. Meanwhile, we demonstrated that MnFe2O4 NPs enhanced K48-linked ubiquitination of GFP-Htt(Q74). Moreover, ubiqinlin-1, but not p62/SQSTM1, served as the ubiquitin receptor that mediated the enhanced degradation of Htt(Q74) by MnFe2O4 NPs. Our findings may have implications for developing novel nanomedicine for the therapy of HD and other polyglutamine expansion diseases.

Effect of alcohol on chronic pelvic pain and prostatic inflammation in a mouse model of experimental autoimmune prostatitis.

BACKGROUND: Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a prevalent disease of the urogenital system. Alcohol has been reported to be closely related to CP/CPPS. Thus, we intended to verify the role of alcohol in CP/CPPS and determine the underlying mechanism. METHODS: We induced experimental autoimmune prostatitis (EAP) mouse model by intradermally injecting a mixture of prostate antigens (PAgs) and complete Freund's adjuvant on days 0 and 28. Mice were treated with alcohol (control-alcohol and EAP-alcohol groups) or vehicle (control-vehicle, and EAP-vehicle groups) from day 32 to 42. Forty-two days after PAg injection, the pathological appearance of the prostate tissues was evaluated, and histological analyses of the prostate were performed. Chronic pelvic pain was assessed by applying von Frey filaments to the lower abdomen. Proinflammatory cytokines were detected by enzyme-linked immunosorbent assay tests. Then, we explored the effects of the NLRP3 inhibitor MCC950 on chronic pelvic pain and prostatic inflammation in this model. RESULTS: Histological analyses showed diffuse inflammation in the stromal tissues that were characterized by severe infiltration of neutrophils and mononuclear cells in mice in the EAP-alcohol group compared with EAP-vehicle group. Chronic pain tests showed that the response frequency was significantly increased using a von Frey filament at forces of 0.4, 1.0, and 4.0 g in EAP-alcohol group compared with EAP-vehicle (P < .05). The levels of proinflammatory cytokines, including interferon (IFN)-γ, tumor necrosis factor (TNF)-α, IL-17, and IL-1ß were all significantly elevated in EAP-alcohol group compared with the EAP-vehicle group (P < .05). However, between the control-alcohol and control-vehicle groups, chronic pain tests, histological assays, and cytokine determinations showed no differences. Furthermore, our results demonstrated that MCC950 could decrease the expression level of NLRP3 inflammasome-related proteins including NLRP3, ASC, and caspase-1. The chronic pain tests, histological assays, and cytokine determinations showed that MCC950 could attenuate the chronic pain and prostatic inflammation through the inhibition of the NLRP3 inflammasome. CONCLUSIONS: This study indicated that alcohol could aggravate the severity of prostatic inflammation in EAP model though activating the NLRP3 inflammasome. Furthermore, the role of MCC950 in inhibiting NLRP3 inflammasome and decreasing IL-1ß secretion to alleviate EAP severity may show that it is a promising therapeutic agent for CP/CPPS.

Atomic Layer Deposited Hf0.5Zr0.5O2-based Flexible Memristor with Short/Long-Term Synaptic Plasticity.

Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.