Cervical cancer biomarker screening based on Raman spectroscopy and multivariate statistical analysis.

Cervical cancer (CC) stands as one of the most prevalent malignancies among females, and the examination of serum tumor markers(TMs) assumes paramount significance in both its diagnosis and treatment. This research delves into the potential of combining Surface-Enhanced Raman Spectroscopy (SERS) with Multivariate Statistical Analysis (MSA) to diagnose cervical cancer, coupled with the identification of prospective serum biomarkers. Serum samples were collected from 95 CC patients and 81 healthy subjects, with subsequent MSA employed to analyze the spectral data.

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

Both and cause an increasing number of diseases in fish, resulting in great economic losses in aquaculture. In addition, the disease infected with or 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.

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.

Antimicrobial activity of phenyllactic acid against Klebsiella pneumoniae and its effect on cell wall membrane and genomic DNA.

As Klebsiella pneumoniae (KP) has acquired high levels of resistance to multiple antibiotics, it is considered a worldwide pathogen of concern, and substitutes for traditional antibiotics are urgently needed. 3-Phenyllactic acid (PLA) has been reported to have antimicrobial activity against food-borne bacteria. However, there was no experiment evidence for the exact antibacterial effect and mechanism of PLA kills pathogenic KP.

Development of a Strategy for L-Lactic Acid Production by Using 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.

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.

Diagnoses in multiple types of cancer based on serum Raman spectroscopy combined with a convolutional neural network: Gastric cancer, colon cancer, rectal cancer, lung cancer.

Cancer is one of the major diseases that seriously threaten human health. Timely screening is beneficial to the cure of cancer. There are some shortcomings in current diagnosis methods, so it is very important to find a low-cost, fast, and nondestructive cancer screening technology.

Isolation and screening of a chitin deacetylase producing and its potential for chitosan preparation.

Chitosan is a biopolymer material extracted from marine biomass waste such as shrimp and crab shells, which has good biocompatibility and degradability with great potential for application in the field of wastewater treatment and soil remediation. The higher the degree of deacetylation (DD), the better the adsorption performance of chitosan. Chitin deacetylase (CDA) can specifically catalyze the deacetylate of chitin in a green reaction that is environmentally friendly.

A classification model for detection of ductal carcinoma in situ by Fourier transform infrared spectroscopy based on deep structured semantic model.

At present, deep learning is widely used in spectral data processing. Deep learning requires a large amount of data for training, while the collection of biological serum spectra is limited by sample numbers and labor costs, so it is impractical to obtain a large amount of serum spectral data for disease detection. In this study, we propose a spectral classification model based on the deep structured semantic model (DSSM) and successfully apply it to Fourier Transform Infrared (FT-IR) spectroscopy for ductal carcinoma in situ (DCIS) detection.

Compared between support vector machine (SVM) and deep belief network (DBN) for multi-classification of Raman spectroscopy for cervical diseases.

In this study, a minimally invasive test method for cervical cancer in vitro was proposed by comparing Raman spectroscopy with support vector machine (SVM) model and deep belief network (DBN) model. The serum Raman spectra of cervical cancer, hysteromyoma, and healthy people were collected. After data processing, SVM classification model and DBN classification model were built respectively.

Simultaneous improvement of the thermostability and activity of lactic dehydrogenase from through rational design.

d-Phenyllactic acid, is a versatile organic acid with wide application prospects in the food, pharmaceutical and material industries. Wild-type lactate dehydrogenase LDH from exhibits a high catalytic performance in the production of d-phenyllactic acid from phenylpyruvic acid or sodium phenylpyruvate, but its industrial application is hampered by poor thermostability. Here, computer aided rational design was applied to improve the thermostability of LDH.

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.

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.

Efficient Co-production of Docosahexaenoic Acid Oil and Carotenoids in Aurantiochytrium sp. Using a Light Intensity Gradient Strategy.

Aurantiochytrium is a promising source of docosahexaenoic acid (DHA) and carotenoids, but their synthesis is influenced by environmental stress factors. In this study, the effect of different light intensities on the fermentation of DHA oil and carotenoids using Aurantiochytrium sp. TZ209 was investigated.

Breast cancer early detection by using Fourier-transform infrared spectroscopy combined with different classification algorithms.

Early detection of breast cancer is of great value in improving the prognosis. The current detection methods of breast cancer have their own limitations. In this study, we investigated the feasibility of Fourier Transform Infrared (FT-IR) spectroscopy combined with different classification algorithms for the early detection of breast cancer in a large sample of 526 patients, including 308 invasive breast cancer, 101 ductal carcinoma in situ, and 117 healthy controls.

Rapid discrimination of hepatic echinococcosis patients' serum using vibrational spectroscopy combined with support vector machines.

Echinococcosis is a severe zoonotic parasitic disease, and it is continuing to be a significant public health issue. The course of the disease is usually slow, and patients often remain asymptomatic for years. There is no standardized and widely accepted treatment, so early and accurate diagnosis is essential.

Rapid detection of hysteromyoma and cervical cancer based on serum surface-enhanced Raman spectroscopy and a support vector machine.

In this study, we investigated the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with a support vector machine (SVM) algorithm to discriminate hysteromyoma and cervical cancer from healthy volunteers rapidly. SERS spectra of serum samples were recorded from 30 hysteromyoma patients, 36 cervical cancer patients as well as 30 healthy subjects. SVM was used to establish the classification models, and three types of kernel functions, namely linear, polynomial, and Gaussian radial basis function (RBF), were utilized for comparison.

Enhanced Antimicrobial Cellulose/Chitosan/ZnO Biodegradable Composite Membrane.

In this study, chitosan and sugarcane cellulose were used as film-forming materials, while the inorganic agent zinc oxide (ZnO) and natural compound phenyllactic acid (PA) were used as the main bacteriostatic components to fabricate biodegradable antimicrobial composite membranes. The water absorption and antimicrobial properties were investigated by adjusting the concentration of PA. The scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) results demonstrated that the components of the composite membrane were successfully integrated.

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.

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.

Functional Analysis of and in Response to Biotic and Abiotic Stresses in Rice.

Mediator complex is a multiprotein complex that regulates RNA polymerase II-mediated transcription. Moreover, it functions in several signaling pathways, including those involved in response to biotic and abiotic stresses. We used virus-induced gene silencing (VIGS) to study the functions of two genes, namely and in response to biotic and abiotic stresses in rice.

Screening of highly effective mixed natural antioxidants to improve the oxidative stability of microalgal DHA-rich oil.

Docosahexaenoic acid (DHA)-rich oil sourced from microalgae can easily become oxidized. The objective of this work was to screen the optimal natural antioxidant mixture for protecting DHA-rich oil. Different natural antioxidants, encompassing tea polyphenols, natural vitamin E, rosemary extract, licorice root antioxidant, ascorbyl palmitate and lecithin were tested individually and in combination in an accelerated oxidation process.

SKIP Silencing Decreased Disease Resistance Against and pv. DC3000 in Tomato.

SKIP, a component of the spliceosome, is involved in numerous signaling pathways. However, there is no direct genetic evidence supporting the function of SKIP in defense responses. In this paper, two , namely, and , were analyzed in tomato.

Combining derivative Raman with autofluorescence to improve the diagnosis performance of echinococcosis.

Echinococcosis is a zoonotic parasitic disease transmitted by animals and distributed all over the world. There is no standardized and widely accepted treatment method, and early and accurate diagnosis is crucial for the prevention and cure of echinococcosis. Here, we explored the feasibility of using derivative Raman in combination with autofluorescence (AF) to improve the diagnosis performance of echinococcosis.