Raman spectroscopy combined with multivariate statistical algorithms for the simultaneous screening of cervical and breast cancers.

Breast and cervical cancers are becoming the leading causes of death among women worldwide, but current diagnostic methods have many drawbacks, such as being time-consuming and high cost. Raman spectroscopy, as a rapid, reliable, and non-destructive spectroscopic detection technique, has achieved many breakthrough results in the screening and prognosis of various cancer tumors. Therefore, in this study, Raman spectroscopy technology was used to diagnose breast cancer and cervical cancer. A total of 225 spectra were recorded from 87 patients with cervical cancer, 60 patients with breast cancer, and 78 healthy individuals. The obvious difference in Raman spectrum between the three groups was mainly shown at 809 cm-1 (tyrosine), 958 cm-1 (carotenoid), 1004 cm-1 (phenylalanine), 1154 cm-1 (ß-carotene), 1267 cm-1 (Amide III), 1445 cm-1 (phospholipids), 1515 cm-1 (ß-carotene), and 1585 cm-1 (C = C olefinic stretch). We used one-way analysis of variance for these peaks and demonstrated that they were significantly different. Then, we combined the detected Raman spectra with multivariate statistical calculations using the principal component analysis-linear discrimination algorithm (PCA-LDA) to discriminate between the three groups of collected serum samples. The diagnostic results showed that the model's accuracy, precision, recall, and F1 score of the model were 92.90%, 92.62%, 92.10%, and 92.36%, respectively. These results suggest that Raman spectroscopy can achieve ultra-sensitive detection of serum, and the developed diagnostic models have great potential for the prognosis and simultaneous screening of cervical and breast cancers.

A Duplex PCR Assay for Rapid Detection of Klebsiella pneumoniae and Chryseobacterium in Large Yellow Croaker Fish.

Both Klebsiella pneumoniae and Chryseobacterium cause an increasing number of diseases in fish, resulting in great economic losses in aquaculture. In addition, the disease infected with Klebsiella pneumoniae or Chryseobacterium exhibited the similar clinical symptoms in aquatic animals. However, there is no effective means for the simultaneous detection of co-infection and discrimination them for these two pathogens. Here, we developed a duplex polymerase chain reaction (PCR) method based on the outer membrane protein A (ompA) gene of Klebsiella pneumoniae and Chryseobacterium. The specificity and validity of the designed primers were confirmed experimentally using simplex PCR. The expected amplicons for Klebsiella pneumoniae and Chryseobacterium had a size of 663 and 1404 bp, respectively. The optimal condition for duplex PCR were determined to encompass a primer concentration of 0.5 µM and annealing temperature of 57°C. This method was analytical specific with no amplification being observed from the genomic DNA of Escherichia coli, Vibrio harveyi, Pseudomonas plecoglossicida, Aeromonas hydrophila and Acinetobacter johnsonii. The limit of detection was estimated to be 20 fg of genomic DNA for Chryseobacterium and 200 fg for Klebsiella pneumoniae, or 100 colony-forming units (CFU) of bacterial cells in both cases. The duplex PCR was capable of simultaneously amplifying target fragments from genomic DNA extracted from the bacteria and fish liver. For practical validation of the method, 20 diseased fish were collected from farms, among which 4 samples were PCR-positive for Klebsiella pneumoniae and Chryseobacterium. The duplex PCR method developed here is time-saving, specific, convenient, and may prove to be an invaluable tool for molecular detection and epidemiological investigation of Klebsiella pneumoniae and Chryseobacterium in the field of aquaculture.

High-definition image transmission through dynamically perturbed multimode fiber by a self-attention based neural network.

We implement faithful multimode fiber (MMF) image transmission by a self-attention-based neural network. Compared with a real-valued artificial neural network (ANN) based on a convolutional neural network (CNN), our method utilizes a self-attention mechanism to achieve a higher image quality. The enhancement measure (EME) and structural similarity (SSIM) of the dataset collected in the experiment improved by 0.79 and 0.04; the total number of parameters can be reduced by up to 25%. To enhance the robustness of the neural network to MMF bending in image transmission, we use a simulation dataset to prove that the hybrid training method is helpful in MMF transmission of a high-definition image. Our findings may pave the way for simpler and more robust single-MMF image transmission schemes with hybrid training; SSIM on datasets under different disturbances improve by 0.18. This system has the potential to be applied to various high-demand image transmission tasks, such as endoscopy.

Development of a Strategy for L-Lactic Acid Production by Rhizopus oryzae Using Zizania latifolia Waste and Cane Molasses as Carbon Sources.

As a biodegradable and renewable material, polylactic acid is considered a major environmentally friendly alternative to petrochemical plastics. Microbial fermentation is the traditional method for lactic acid production, but it is still too expensive to compete with the petrochemical industry. Agro-industrial wastes are generated from the food and agricultural industries and agricultural practices. The utilization of agro-industrial wastes is an important way to reduce costs, save energy and achieve sustainable development. The present study aimed to develop a method for the valorization of Zizania latifolia waste and cane molasses as carbon sources for L-lactic acid fermentation using Rhizopus oryzae LA-UN-1. The results showed that xylose derived from the acid hydrolysis of Z. latifolia waste was beneficial for cell growth, while glucose from the acid hydrolysis of Z. latifolia waste and mixed sugars (glucose and fructose) from the acid hydrolysis of cane molasses were suitable for the accumulation of lactic acid. Thus, a three-stage carbon source utilization strategy was developed, which markedly improved lactic acid production and productivity, respectively reaching 129.47 g/L and 1.51 g/L·h after 86 h of fermentation. This work demonstrates that inexpensive Z. latifolia waste and cane molasses can be suitable carbon sources for lactic acid production, offering an efficient utilization strategy for agro-industrial wastes.

Edge detection in single multimode fiber imaging based on deep learning.

We propose a new edge detection scheme based on deep learning in single multimode fiber imaging. In this scheme, we creatively design a novel neural network, whose input is a one-dimensional light intensity sequence, and the output is the edge detection result of the target. Different from the traditional scheme, we can directly obtain the edge information of unknown objects by using this neural network without rebuilding the image. Simulation and experimental results show that, compared with the traditional method, this method can get better edge details, especially in the case of low sampling rates. It can increase the structural similarity index of edge detection imaging from 0.38 to 0.62 at the sampling rate of 0.6%. At the same time, the robustness of the method to fiber bending is also proved. This scheme improves the edge detection performance of endoscopic images and provides a promising way for the practical application of multimode fiber endoscopy.

Using FADOF to eliminate the background light influence in ghost imaging.

The high solar background during the day adversely affects the long distance daytime operations of ghost imaging. It is extremely hard to distinguish the signal light from the background noise light after they are both converted to voltage or current signals by the bucket detector, so spectral filtering before the detector is quite important. In this work, a Faraday anomalous dispersion optical filter (FADOF) is used in eliminating the background light influence in ghost imaging. Results of lab experiment show that the background light noise tolerance of the ghost imaging with FADOF is at least 18 times bigger than that with a 10 nm optical filter. The method has simple structure, great performance and great algorithms compatibility.

Clustering-based CLEAN algorithm in ghost imaging with sparse spatial frequencies.

When insufficient samples in the spatial frequency domain could be effectively compensated by the modified CLEAN algorithm, a novel aperture-synthetic scheme of ghost imaging takes advantage of a superior speed of modulation and an enhancement on the spatial resolution. However, there still exist some imperfections in the modified CLEAN reconstructions, such as the fact that some omitted scatter noise still remains or the object contour may be incomplete. Therefore, we optimize the modified CLEAN algorithm by proposing a density clustering algorithm to overcome these drawbacks and improve the visual quality.

Thermal and temporal characteristics of Faraday anomalous dispersion optical filters based on a hollow cathode lamp.

As a new, to the best of our knowledge, alternative to the saturated vapor-cell-based Faraday anomalous dispersion optical filter (FADOF), the FADOF based on a hollow cathode lamp (HCL-FADOF) not only enables the FADOF to work normally at room temperature without heating, but also has some new features due to the inherent characteristics of the HCL. In this Letter, we implement an HCL-FADOF operating on the rubidium D2 line and experimentally investigate the effect of ambient temperature on its performance and cold-start characteristics. Results show that the HCL-FADOF can provide excellent stability within a large temperature range, even at temperatures below 0°C. A comparison of the start performance between the HCL-FADOF and FADOF using saturated vapor cells is also provided. This work shows unique features of the HCL-FADOF in a low-temperature environment and its quick-start advantage, which provides a solid foundation for extensive applications.

Compressive endoscopic imaging with complementary light modulation.

We propose an effective endoscopic imaging method utilizing compressive sensing (CS) theory on the basis of complementary light modulation of a spatial light modulator. Both the simulated and the experimental results show that complementary compressive sensing (CCS) always needs less time to obtain better work than conventional CS with normal modulation at the same sampling rate. First, the speed of CCS is at least twice as fast as CS. Second, in comparison with CS, CCS can improve the signal-to-noise ratio of the reconstructed image by 49.7%, which indicates that this method is of great significance to endoscopic applications in terms of image fidelity and denoising performance.

Image recovery of ghost imaging with sparse spatial frequencies.

When the spatial frequencies of the object are insufficiently sampled, the reconstruction of ghost imaging will suffer from repetitive visual artifacts, which cannot be effectively tackled by existing ghost imaging reconstruction techniques. In this Letter, extensions of the CLEAN algorithm applied in ghost imaging are explored to eliminate those artifacts. Combined with the point spread function estimation using the second-order coherence measurement in ghost imaging, our modified CLEAN algorithm is demonstrated to have a fast and noteworthy improvement against the spatial-frequency insufficiency, even for the extreme sparse sampling cases. A brief explanation of the algorithm and performance analysis are given.

Orthonormalization method in ghost imaging.

Ghost imaging system requires a large number of samples to reconstruct the object. Computational ghost imaging can use well-designed pre-modulated orthogonal patterns to reduce the requirement of sampling number and increase the imaging quality, while the rotating ground glass (RGG) scheme cannot. Instead of the pre-modulation method, a post-processing method using Gram-Schmidt process to orthonormalize the patterns in a RGG scheme is introduced. Reconstructed ghost image after the Gram-Schmidt process (SGI) are tested using the quality indicators such as the Contrast-to-Noise (CNR), the Peak Signal to Noise Ratio (PSNR), the Correlation Coefficient (CC) and reducing the Mean Square Error (MSE). Simulation results show that this method has obvious advantage on enhancing the efficiency of image acquisition, and the sampling number requirement drops from several thousands to a few hundreds in ideal condition. However, in actual system with noise, the image quality from SGI declines in large sampling number, for noise and errors accumulate in the orthonormalization process. So an improved Group SGI method is then developed to avoid this error accumulation, which behaves effectively in reconstructing the image from experimental data and show good performances in large sampling number too. Since this method do not change the relationship between the reference patterns and the bucket values, it can easily combine with most of reconstruction algorithms and improve their reconstruction efficiency.

The complete genome sequence of Bacillus halotolerans ZB201702 isolated from a drought- and salt-stressed rhizosphere soil.

Bacillus halotolerans is a rhizobacterium with the potential to promote plant growth and tolerance to drought and salinity stress. Here, we present the complete genome sequence of B. halotolerans ZB201702, which consists of 4,150,000 bp in a linear chromosome, including 3074 protein-coding sequences, 30 rRNAs, and 85 tRNAs. Genome analysis revealed many putative gene clusters involved in defense mechanisms. Activity analysis of the strain under salt and simulated drought stress suggests tolerance to abiotic stresses. The complete genome information of B. halotolerans ZB201702 could provide valuable insights into rhizobacteria-mediated plant salt and drought tolerance and rhizobacteria-based solutions for abiotic stress agriculture.

Signal intensity influences on the atomic Faraday filter.

Previous studies of the Faraday anomalous dispersion optical filter (FADOF) mainly focus on the weak signal light filtering, without regard for the influences of the signal light intensity on the filter itself. However, in some applications the signal light is strong enough to change the filter's performance. In this work, the influences of the signal light intensity on the transmittance spectrum is experimentally investigated in a 780 nm Rb85 FADOF in both the line-center and wings operation modes. The results show that the transmittance spectrum varies significantly with the signal light intensity. As the signal light increases, some existing transmittance peaks decline, some new transmittance peaks appear, and the maximum transmittance peak frequency may change. The spectrum in strong signal lights can be quite different from those calculated by programs in the condition of weak signal lights. These results are important for applications of the FADOF in the condition of strong signal lights.

An optimized fed-batch culture strategy integrated with a one-step fermentation improves L-lactic acid production by Rhizopus oryzae.

In previous work, we proposed a novel modified one-step fermentation fed-batch strategy to efficiently generate L-lactic acid (L-LA) using Rhizopus oryzae. In this study, to further enhance efficiency of L-LA production through one-step fermentation in fed-batch cultures, we systematically investigated the initial peptone- and glucose-feeding approaches, including different initial peptone and glucose concentrations and maintained residual glucose levels. Based on the results of this study, culturing R. oryzae with initial peptone and glucose concentrations of 3.0 and 50.0 g/l, respectively, using a fed-batch strategy is an effective approach of producing L-LA through one-step fermentation. Changing the residual glucose had no obvious effect on the generation of L-LA. We determined the maximum LA production and productivity to be 162 g/l and 6.23 g/(l·h), respectively, during the acid production stage. Compared to our previous work, there was almost no change in L-LA production or yield; however, the productivity of L-LA increased by 14.3%.

Image quality recovery in binary ghost imaging by adding random noise.

When the sampling data of ghost imaging are recorded with less bits, i.e., experiencing quantization, a decline in image quality is observed. The fewer bits that are used, the worse the image one gets. Dithering, which adds suitable random noise to the raw data before quantization, is proved to be capable of compensating image quality decline effectively, even for the extreme binary sampling case. A brief explanation and parameter optimization of dithering are given.

High-level expression and purification of a molluskan endoglucanase from Ampullaria crossean in Pichia pastoris.

EG27I is an endogenous glucanase belonging to glycoside hydrolase family (GHF) 45 from the mollusk Ampullaria crossean. In this study, the mature EG27I peptide gene fused to the HFBII secretion signal of Trichoderma reesei was expressed under the GAP promoter of Pichia pastoris in SMD1163 strain. A bioactive EG27I with a molecular weight of 27 kDa was successfully expressed and secreted into our culture medium. The respective final OD600 and hydrolytic activity were 333 and 1.28 U/mL when high-cell-density fermentation of the recombinant P. pastoris was performed in a 7.5 L fermenter through a fed-batch strategy for 132 h. The recombinant protein concentration of the fermentation supernatant was 47.7 mg/L. EG27I was consecutively purified from the fermentation supernatant through ultrafiltration, cation exchange, and hydrophobic interaction. The specific activity of the recombinant EG27I was 26.8 U/mg, and the optimal pH and temperature of the enzyme were 5 and 50 °C, respectively. The half-life of the enzyme activity at 100 °C could reach 40 min. The N-terminal amino acid sequence analysis of the purified recombinant protein confirmed that the amino terminal sequence was consistent with the natural structure. The high quantity and purity of the EG27I provide a basis for future structural and functional studies.

Analysis of excited-state Faraday anomalous dispersion optical filter at 1529 nm.

In this work, a detailed theoretical analysis of 1529 nm ES-FADOF (excited state Faraday anomalous dispersion optical filter) based on rubidium atoms pumped by 780 nm laser is introduced, where Zeeman splitting, Doppler broadening, and relaxation processes are considered. Experimental results are carefully compared with the derivation. The results prove that the optimal pumping frequency is affected by the working magnetic field. The population distribution among all hyperfine Zeeman sublevels under the optimal pumping frequency has also been obtained, which shows that 85Rb atoms are the main contribution to the population. The peak transmittance above 90% is obtained, which is in accordance with the experiment. The calculation also shows that the asymmetric spectra observed in the experiment are caused by the unbalanced population distribution among Zeeman sublevels. This theoretical model can be used for all kinds of calculations for FADOF.

Tunable rubidium excited state Voigt atomic optical filter.

A tunable rubidium excited state Voigt atomic optical filter working at optical communication wavelength (1.5 µm) is realized. The filter achieves a peak transmittance of 57.6% with a double-peak structure, in which each one has a bandwidth of 600 MHz. Benefiting from the Voigt type structure, the magnetic field of the filter can be tuned from 0 to 1600 gauss, and a peak transmittance tunability of 1.6 GHz can thus be realized. Different from the excited state Faraday type filter, the pump efficiency in the Voigt filter is affected a lot by the pump polarization. Measured absorption results of the pump laser and transmittances of the signal laser both prove that the vertical linear polarization pumping is the most efficient in the Voigt filter.

An atomic optical filter working at 1.5 µm based on internal frequency stabilized laser pumping.

An excited state Faraday anomalous dispersion optical filter (ES-FADOF) working at the optical communication wavelength (1.5 µm) is realized. Unlike the usual ES-FADOF schemes using an external frequency stabilization, an internal frequency stabilization scheme is proposed and the working atoms inside the filter are adopted as the reference. A particular cross line of multiple transitions is used for the frequency stabilization for the pump laser and thus, a higher pump efficiency is achieved. For example, compared with previous ES-FADOF schemes, this method can increase the transmittance from 10% to 60% at 100 °C. Moreover, in this scheme, the external frequency stabilization is not necessary and the volume of the atomic filter can be reduced. This simplifies the whole structure and a compact ES-FADOF can thus be realized.

Excited state Faraday anomalous dispersion optical filters based on indirect laser pumping.

The direct pump method now used in excited state Faraday anomalous dispersion optical filters (ES-FADOFs) requires that the transition between the target and the ground state is an electric dipole allowed transition and that a laser that operates at the exact pump wavelength is available. This is not always satisfied in practice. An indirect laser pump method for ES-FADOF is proposed and experimentally realized. Compared with the commonly used direct pump method, this indirect pump method can reach the same performance using lasers at very different wavelengths. This method can greatly extend the wavelength range of FADOF and provide a novel scheme for ES-FADOF design.