Screening, identification, and mechanism analysis of starch-degrading bacteria during curing process in tobacco leaf

Tobacco, a vital economic crop, had its quality post-curing significantly influenced by starch content. Nonetheless, the existing process parameters during curing were inadequate to satisfy the starch degradation requirements. Microorganisms exhibit inherent advantages in starch degradation, offering significant potential in the tobacco curing process. Our study concentrated on the microbial populations on the surface of tobacco leaves and in the rhizosphere soil. A strain capable of starch degradation, designated as BS3, was successfully isolated and identified as Bacillus subtilis by phylogenetic tree analysis based on 16SrDNA sequence. The application of BS3 on tobacco significantly enhanced enzyme activity and accelerated starch degradation during the curing process. Furthermore, analyses of the metagenome, transcriptome, and metabolome indicated that the BS3 strain facilitated starch degradation by regulating surface microbiota composition and affecting genes related to starch hydrolyzed protein and key metabolites in tobacco leaves. This study offered new strategies for efficiently improving the quality of tobacco leaves

New insights into a microvascular invasion prediction model in hepatocellular carcinoma: A retrospective study from the SEER database and China

Background and AimsThe prognosis of liver cancer is strongly influenced by microvascular infiltration (MVI). Accurate preoperative MVI prediction can aid clinicians in the selection of suitable treatment options. In this study, we constructed a novel, reliable, and adaptable nomogram for predicting MVI.MethodsUsing the Surveillance, Epidemiology, and End Results (SEER) database, we extracted the clinical data of 1,063 patients diagnosed with hepatocellular carcinoma (HCC) and divided it into either a training (n = 739) or an internal validation cohort (n = 326). Based on multivariate analysis, the training cohort data were analyzed and a nomogram was generated for MVI prediction. This was further verified using an internal validation cohort and an external validation cohort involving 293 Chinese patients. Furthermore, to evaluate the efficacy, accuracy, and clinical use of the nomogram, we used concordance index (C-index), calibration curve, and decision curve analysis (DCA) techniques.ResultsIn accordance with the multivariate analysis, tumor size, tumor number, alpha-fetoprotein (AFP), and histological grade were independently associated with MVI. The established model exhibited satisfactory performance in predicting MVI. The C-indices were 0.719, 0.704, and 0.718 in the training, internal validation, and external validation cohorts, respectively. The calibration curves showed an excellent consistency between the predictions and actual observations. Finally, DCA demonstrated that the newly developed nomogram had favorable clinical utility.ConclusionsWe established and verified a novel preoperative MVI prediction model in HCC patients. This model can be a beneficial tool for clinicians in selecting an optimal treatment plan for HCC patients

Excessively tilted fiber grating based Fe3O4 saturable absorber for passively mode-locked fiber laser

A novel approach to saturable absorber (SA) formation is presented by taking advantage of the mode coupling property of excessively tilted fiber grating (Ex-TFG). Stable mode-locked operation can be conveniently achieved based on the interaction between Ex- TFG coupled light and deposited ferroferric-oxide (Fe3O4) nanoparticles. The central wavelength, bandwidth and single pulse duration of the output are 1595 nm, 4.05 nm, and 912 fs, respectively. The fiber laser exhibits good long-term stability with signal-to-noise ratio (SNR) of 67 dB. For the first time, to the best of our knowledge, Ex-TFG based Fe3O4 SA for mode-locked fiber laser is demonstrated

Degradation and mechanism analysis of protein macromolecules by functional bacteria in tobacco leaves

Tobacco, a crop of significant economic importance, was greatly influenced in leaf quality by protein content. However, current processing parameters fail to adequately meet the requirements for protein degradation. Microorganisms possess potential advantages for degrading proteins and enhancing the quality of tobacco leaves, and hold substantial potential in the process of curing. To effectively reduce the protein content in tobacco leaves, thereby improving the quality and safety of the tobacco leaves. In this study, tobacco leaf were used as experimental material. From these, the BSP1 strain capable of effectively degrading proteins was isolated and identified as Bacillus subtilis by 16S rDNA analysis. Furthermore, the mechanisms were analyzed by integrating microbiome, transcriptome, and metabolome. Before curing, BSP1 was applied to the surface of tobacco leaves. The results indicated that BSP1 effectively improves the activity of key enzymes and the content of related substances, thereby enhancing protein degradation. Additionally, protein degradation was achieved by regulating the diversity of the microbial community on the surface of the tobacco leaves and the ubiquitin-proteasome pathway. This study provided new strategies for extracting and utilizing functional strains from tobacco leaves, opening new avenues for enhancing the quality of tobacco leaves

Memory Access Optimization of a Neural Network Accelerator Based on Memory Controller

Special accelerator architecture has achieved great success in processor architecture, and it is trending in computer architecture development. However, as the memory access pattern of an accelerator is relatively complicated, the memory access performance is relatively poor, limiting the overall performance improvement of hardware accelerators. Moreover, memory controllers for hardware accelerators have been scarcely researched. We consider that a special accelerator memory controller is essential for improving the memory access performance. To this end, we propose a dynamic random access memory (DRAM) memory controller called NNAMC for neural network accelerators, which monitors the memory access stream of an accelerator and transfers it to the optimal address mapping scheme bank based on the memory access characteristics. NNAMC includes a stream access prediction unit (SAPU) that analyzes the type of data stream accessed by the accelerator via hardware, and designs the address mapping for different banks using a bank partitioning model (BPM). The image mapping method and hardware architecture were analyzed in a practical neural network accelerator. In the experiment, NNAMC achieved significantly lower access latency of the hardware accelerator than the competing address mapping schemes, increased the row buffer hit ratio by 13.68% on average (up to 26.17%), reduced the system access latency by 26.3% on average (up to 37.68%), and lowered the hardware cost. In addition, we also confirmed that NNAMC efficiently adapted to different network parameters

Genome-Wide Screening Identifies Prognostic Long Noncoding RNAs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignancy with a poor prognosis. Therefore, there is an urgent call for the investigation of novel biomarkers in HCC. In the present study, we identified 6 upregulated lncRNAs in HCC, including LINC01134, RHPN1-AS1, NRAV, CMB9-22P13.1, MKLN1-AS, and MAPKAPK5-AS1. Higher expression of these lncRNAs was correlated to a more advanced cancer stage and a poorer prognosis in HCC patients. Enrichment analysis revealed that these lncRNAs played a crucial role in HCC progression, possibly through a series of cancer-related biological processes, such as cell cycle, DNA replication, histone acetyltransferase complex, fatty acid oxidation, and lipid modification. Moreover, competing endogenous RNA (ceRNA) network analysis revealed that these lncRNAs could bind to certain miRNAs to promote HCC progression. Loss-of-function assays indicated that silencing of RHPN1-AS1 significantly suppressed HCC proliferation and migration. Though further validations are still needed, these identified lncRNAs could serve as valuable potential biomarkers for HCC prognosis

A 20 W, Less-Than-1-kHz Linewidth Linearly Polarized All-Fiber Laser

We report a continuous-wave high-output power and narrow-linewidth all-fiber laser at 1550 nm with the master oscillator power amplifier (MOPA) configuration. An all-fiber distributed feedback seed laser was boosted by three cascaded fiber amplifiers. In the experiment, we adopted a large-mode-area (LMA) Er3+:Yb3+-co-doped polarization-maintaining fiber to increase nonlinear thresholds and avoided the broadening of the laser linewidth. A linear-polarization fiber laser with average output power of 20 W, linewidth of 0.88 kHz, and power jitter less than 2% was finally achieved