Suspected coexistence of perianal necrotizing sweet syndrome in chronic myelomonocytic leukemia: A case report.

BACKGROUND: Chronic myelomonocytic leukemia (CMML) complicated with Sweet syndrome (SS) is a rare hematological neoplasm. However, cases of concomitant development of perianal necrotizing SS (NSS) have not been reported. CASE SUMMARY: We report a case of a 49-year-old male patient who underwent sequential procedures for hemorrhoids and perianal abscess. He developed postoperative incision infection and was referred to the department where the authors work. Initially, perianal necrotizing fasciitis secondary to incision infection after perianal abscess surgery was suspected. Despite receiving antibiotic therapy and undergoing surgical debridement, deeper necrotic areas formed in the patient's perianal wounds, accompanied by persistent high fever. Blood and fungal cultures yielded negative results. The final diagnosis was corrected to be CMML with suspected concomitant perianal NSS. CONCLUSION: CMML with perianal NSS is a rare condition, often misdiagnosed as perianal abscess or perianal necrotizing fasciitis. Conventional antibiotic therapy and surgical debridement are ineffective in managing this condition.

Terahertz Spectroscopy and Imaging Techniques for Herbal Medicinal Plants Detection: A Comprehensive Review.

Herbal medicine (HM), derived from various therapeutic plants, has garnered considerable attention for its remarkable effectiveness in treating diseases. However, numerous issues including improved varieties selection, hazardous residue detection, and concoction management affect herb quality throughout the manufacturing process. Therefore, a practical, rapid, nondestructive detection technology is necessary. Terahertz (THz) spectroscopy, with low energy, penetration, and fingerprint features, becomes preferable method for herb quality appraisal. There are three parts in our review. THz techniques, data processing, and modeling methods were introduced in Part I. Three primary applications (authenticity, composition and active ingredients, and origin detection) of THz in medicinal plants quality detection in industrial processing and marketing were detailed in Part II. A thorough investigation and outlook on the well-known applications and advancements of this field were presented in Part III. This review aims to bring new enlightenment to the in-depth THz application research in herbal medicinal plants.

Modified ultrasound scalpel haemorrhoidectomy versus conventional haemorrhoidectomy for mixed haemorrhoids: a study protocol for a single-blind randomised controlled trial.

BACKGROUND: Haemorrhoids are common and frequently occurring diseases in the clinical setting, and severe haemorrhoids require surgical treatment. There are various surgical methods to treat haemorrhoids, but each has advantages and disadvantages. In recent years, ultrasonic scalpels have been used in haemorrhoid surgery and have achieved good results. Ultrasonic scalpel haemorrhoidectomy is safer and more effective in the surgical treatment of grade III and IV haemorrhoids, with less intraoperative bleeding, less postoperative pain, and fewer complications than diathermic therapy, electrosurgical haemorrhoidectomy, PROXIMATE® PPH haemorrhoidal circular stapler haemorrhoidopexy (PPH), and traditional haemorrhoidectomy. In previous reports, the majority of ultrasonic scalpel haemorrhoidectomies were performed as open procedures, with only the body of the haemorrhoid removed with the ultrasonic scalpel and the wound left open for drainage and natural healing. However, we performed a preliminary experiment with 12 patients who underwent open ultrasonic scalpel haemorrhoidectomy in the early stage. The results showed that 8 patients had different degrees of postoperative bleeding, and 4 of them required a second haemostatic surgery under anaesthesia. Therefore, we modified the open ultrasonic scalpel haemorrhoidectomy procedure by removing the mucosa of the internal haemorrhoid and closing the base of the incision with figure-eight penetrating sutures and designed this study protocol to evaluate its clinical efficacy and safety. METHODS: A randomised single-blind parallel-controlled trial is proposed for this project, and patients who meet the inclusion criteria will be divided into a test group and a control group, with 39 patients in each group. The experimental group will be treated with modified ultrasonic scalpel haemorrhoidectomy, and the control group will be treated with the Milligan-Morgan operation. The effectiveness of modified ultrasonic scalpel haemorrhoidectomy for haemorrhoids will be objectively evaluated, including the incision healing time and the time for patients to return to normal activities, postoperative complications, evaluations of anal function 3 months and 6 months after surgery, an evaluation of quality of life 6 months after surgery, and an evaluation of the patient satisfaction rate 6 months after surgery. The safety assessment will consider all adverse and serious adverse events associated with the study treatment. DISCUSSION: The study was approved by the ethics committee. The first patient was registered on July 1 2021. The purpose of this trial will be to evaluate the clinical efficacy and safety of the modified ultrasonic scalpel haemorrhoidectomy procedure for the treatment of mixed haemorrhoids and to provide an evidence base for the clinical promotion and application of the procedure. A limitation of this study is that only the patients will be single-blinded because the researchers and the patients cannot be blinded at the same time, which may produce certain bias in the results. In addition, the sample size of this study will be small, and the test results will only represent the findings from this clinical trial. In later stages, the sample size needs to be further expanded to improve the level of evidence. Despite its limitations, we hope the present study will help provide a more optimised surgical approach in the selection of haemorrhoid surgery. TRIAL REGISTRATION: Chinese Clinical Trial Registry (Registration ID: ChiCTR2100047229). Registered on June 11, 2021.

Rapid qualitative detection of titanium dioxide adulteration in persimmon icing using portable Raman spectrometer and Machine learning.

Persimmon icing is the white crystalline powder that adheres to the surface of persimmon cakes when the sugar in the persimmon spills over during processing, which is considered the essence of persimmon. Titanium dioxide is a food additive that is commonly added to the surface of persimmon cakes to impersonate high-quality persimmon cakes. However, excessive titanium dioxide can be harmful to humans, so a quick method is needed to identify persimmon cakes as adulterated. Raman spectroscopy with distinctive advantages of water-insensitivity, real-time, field-deployable, label-free, and fingerprinting-identification has been rapidly developed and used in food quality assurance and safety monitoring. In this study, we investigated Raman spectroscopy integrated with machine learning to assess titanium dioxide adulteration in dried persimmon icing. The adaptive iterative reweighting partial least squares (air-PLS) algorithm as an effective algorithm was used to remove fluorescent background signals in raw Raman spectroscopy. Principal components analysis (PCA) was employed to analyze the spectral data and determine the class memberships, and results showed that 99.9% of information could be explained by PC-1 and PC-2. Compared with extreme learning machine (ELM), support vector machine (SVM), back propagation artificial neural network (BP-ANN), and random forest (RF) models, one-dimensional stack auto encoder convolutional neural network (1D-SAE-CNN) could provide the highest detection accuracy of 0.9825, precision of 0.9824, recall of 0.9825, and f1-score of 0.9824. This study shows that Raman spectroscopy coupled with 1D-SAE-CNN is a promising method to detect titanium dioxide adulteration in persimmon icing.

Optical imaging spectroscopy coupled with machine learning for detecting heavy metal of plants: A review.

Heavy metal elements, which inhibit plant development by destroying cell structure and wilting leaves, are easily absorbed by plants and eventually threaten human health via the food chain. Recently, with the increasing precision and refinement of optical instruments, optical imaging spectroscopy has gradually been applied to the detection and reaction of heavy metals in plants due to its in-situ, real-time, and simple operation compared with traditional chemical analysis methods. Moreover, the emergence of machine learning helps improve detection accuracy, making optical imaging spectroscopy comparable to conventional chemical analysis methods in some situations. This review (a): summarizes the progress of advanced optical imaging spectroscopy techniques coupled with artificial neural network algorithms for plant heavy metal detection over ten years from 2012-2022; (b) briefly describes and compares the principles and characteristics of spectroscopy and traditional chemical techniques applied to plants heavy metal detection, and the advantages of artificial neural network techniques including machine learning and deep learning techniques in combination with spectroscopy; (c) proposes the solutions such as coupling with other analytical and detection methods, portability, to address the challenges of unsatisfactory sensitivity of optical imaging spectroscopy and expensive instruments.

Collinear double-pulse laser-induced breakdown spectroscopy based Cd profiling in the soil.

Cadmium (Cd) can migrate in the soil and is readily absorbed by crops. High Cd accumulated in grains poses a huge threat to human health by inhibiting the function of the kidney system. Thus, it is crucial to reveal the content of soil Cd in vertical-depth series using a fast, real-time, and reliable method. For this purpose, laser-induced breakdown spectroscopy (LIBS) combined with multivariate chemometrics was developed to analyze Cd content in the soil with vertical-depth series. Soil samples spiked with different levels of Cd were prepared, and LIBS spectra were obtained by single-pulse LIBS (SP-LIBS) and collinear double-pulse LIBS (CDP-LIBS) with wavelengths of 532 nm and 1064 nm. With appropriate parameters, CDP-LIBS showed better performance in detecting Cd than SP-LIBS. Partial least squares regression (PLSR), genetic algorithm (GA)-optimized back propagation artificial neural network (BP-ANN), and particle swarm optimization (PSO)-optimized least squares-support vector machine (LS-SVM) were tested for quantitative analysis of the spectra after median absolute deviation (MAD), multiple scattering correction (MSC), wavelet transform (WT), spectral averaging, and normalization. PSO-optimized LS-SVM yielded an ideal result, with a coefficient of determination (R2, 0.999) and root mean square error (RMSE, 0.359 mg/Kg) in the prediction dataset. Finally, CDP-LIBS coupled with PSO-optimized LS-SVM was employed to analyze soil Cd content in vertical-depth series to reveal the migration pattern of Cd. Our results indicated that soil Cd had a significant positive relationship with the inverse of soil depth. However, Cd was mainly concentrated in 0-20 cm and rarely leached below 45 cm in the soil. This study suggests that LIBS and its enhancement techniques provide a reliable method for revealing the content of soil Cd in vertical-depth series.

Enhanced Laser-Induced Breakdown Spectroscopy for Heavy Metal Detection in Agriculture: A Review.

Heavy metal pollution in agriculture is a significant problem that endangers human health. Laser-induced breakdown spectroscopy (LIBS) is an emerging technique for material and elemental analysis, especially heavy metals, based on atomic emission spectroscopy. The LIBS technique has been widely used for rapid detection of heavy metals with its advantages of convenient operation, simultaneous detection of multi-elements, wide range of elements, and no requirement for the state and quantity of samples. However, the development of LIBS is limited by its detection sensitivity and limit of detection (LOD). Therefore, in order to improve the detection sensitivity and LOD of LIBS, it is necessary to enhance the LIBS signal to achieve the purpose of detecting heavy metal elements in agriculture. This review mainly introduces the basic instruments and principles of LIBS and summarizes the methods of enhanced LIBS signal detection of heavy metal elements in agriculture over the past 10 years. The three main approaches to enhancing LIBS are sample pretreatment, adding laser pulses, and using auxiliary devices. An enhanced LIBS signal may improve the LOD of heavy metal elements in agriculture and the sensitivity and stability of the LIBS technique. The enhanced LIBS technique will have a broader prospect in agricultural heavy metal monitoring and can provide technical support for developing heavy metal detection instruments.

Surface-Enhanced Raman Scattering Spectroscopy Combined With Chemical Imaging Analysis for Detecting Apple Valsa Canker at an Early Stage.

Apple Valsa canker (AVC) with early incubation characteristics is a severe apple tree disease, resulting in significant orchards yield loss. Early detection of the infected trees is critical to prevent the disease from rapidly developing. Surface-enhanced Raman Scattering (SERS) spectroscopy with simplifies detection procedures and improves detection efficiency is a potential method for AVC detection. In this study, AVC early infected detection was proposed by combining SERS spectroscopy with the chemometrics methods and machine learning algorithms, and chemical distribution imaging was successfully applied to the analysis of disease dynamics. Results showed that the samples of healthy, early disease, and late disease sample datasets demonstrated significant clustering effects. The adaptive iterative reweighted penalized least squares (air-PLS) algorithm was used as the best baseline correction method to eliminate the interference of baseline shifts. The BP-ANN, ELM, Random Forest, and LS-SVM machine learning algorithms incorporating optimal spectral variables were utilized to establish discriminative models to detect of the AVC disease stage. The accuracy of these models was above 90%. SERS chemical imaging results showed that cellulose and lignin were significantly reduced at the phloem disease-health junction under AVC stress. These results suggested that SERS spectroscopy combined with chemical imaging analysis for early detection of the AVC disease was feasible and promising. This study provided a practical method for the rapidly diagnosing of apple orchard diseases.

The development and application of advanced analytical methods in microplastics contamination detection: A critical review.

Microplastics have gradually become emerging environmental contaminants for their extensive distribution, small particle size, and harmful effects on organisms. Therefore, finding accurate, efficient, and rapid analytical methods for detecting microplastics pollution has become an urgent problem. We reviewed the derivation, transport, and classification of microplastics and then highlighted the harmfulness of microplastics which would bring microplastics pollution to the environment and potential damage to organisms. Further, various analytical methods were classified into the thermal analytical method, spectral analytical approach, and other analytical methods based on detection principles. In addition, the application of each analytical method in sea and soil was concluded in detail, and the promising development prospect of each analytical method was discussed. In the end, the chemical analytical method was proposed to explore further in the direction of no sample preparation, nondestructive analysis, low detection limit and it is crucial to establish a unified detection and identification method for microplastics in different environments.

Heavy metal Hg stress detection in tobacco plant using hyperspectral sensing and data-driven machine learning methods.

Accurate detection of heavy metal stress on the growth status of plants is of great concern for agricultural production and management, food security, and ecological environment. A proximal hyperspectral imaging (HSI) system covered the visible/near-infrared (Vis/NIR) region of 400-1000 nm coupled with machine learning methods were employed to discriminate the tobacco plants stressed by different concentration of heavy metal Hg. After acquiring hyperspectral images of tobacco plants stressed by heavy metal Hg with concentration solutions of 0 mg·L-1 (non-stressed groups), 1, 3, and 5 mg·L-1 (3 stressed groups), regions of interest (ROIs) of canopy in tobacco plants were identified for spectra processing. Meanwhile, tobacco plant's appearance and microstructure of mesophyll tissue in tobacco leaves were analyzed. After that, clustering effects of the non-stressed and stressed groups were revealed by score plots and score images calculated by principal component analysis (PCA). Then, loadings of PCA and competitive adaptive reweighted sampling (CARS) algorithm were employed to pick effective wavelengths (EWs) for discriminating non-stressed and stressed samples. Partial least squares discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) were utilized to estimate the stressed tobacco plants status with different concentrations Hg solutions. The performances of those models were evaluated using confusion matrixes (CMes) and receiver operating characteristics (ROC) curves. Results demonstrated that PLS-DA models failed to offer relatively good result, and this algorithm was abandoned to classify the stressed and non-stressed groups of tobacco plants. Compared to LS-SVM model based on full spectra (FS-LS-SVM), the LS-SVM model established EWs selected by CARS (CARS-LS-SVM) carried 13 variables provided an accuracy of 100%, which was promising to achieve the qualitative discrimination of the non-stressed and stressed tobacco plants. Meanwhile, for revealing the discrepancy between 3 stressed groups of tobacco plants, the other FS-LS-SVM, PCA-LS-SVM, and CARS-LS-SVM models were setup and offered relatively low accuracies of 55.56%, 51.11% and 66.67%, respectively. Performance of those 3 LS-SVM discriminative models was also poorly performing to differentiate 3 stressed groups of tobacco plants, which might be caused by low concentration of heavy metal and similar canopy (especially in fresh leaves) of plant. The achievements of the research indicated that HSI coupled with machine learning methods had a powerful potential to discriminate tobacco plant stressed by heavy metal Hg.

Modified Van Assche magnetic resonance imaging-based score for assessing the clinical status of anal fistulas.

The modified Van Assche magnetic resonance imaging (MRI)-based score is a feasible system to assess the clinical status of anal fistulas in Crohn disease. In this study, we evaluated this score's association with clinical status in patients with anal fistulas (AFs).We included all patients with AF who underwent contrast-enhanced pelvic MRI and surgery between January 2011 and December 2016. The score was evaluated retrospectively preoperatively and 1, 3, and 6 months postoperatively. Univariate and multivariate analyses of the risk factors for AF recurrence were also performed.We retrospectively analyzed data for 104 patients. Twelve (11.5%) patients developed AF recurrence. We classified patients' preoperative clinical status into three grades: 52 (50.0%) grade A, 31 (29.8%) grade B, and 21 (20.2%) grade C. The preoperative MRI-based score was significantly correlated with patients' preoperative clinical status grade (Pearson correlation: 0.547; P < .001). The 3 preoperative clinical status grades showed significant (F = 23.303, P < .001) tendencies for associations with lower respective MRI-based scores. The incidence of AF recurrence decreased with the MRI-based score to 1-month postoperatively, then gradually increased (F = 60.863, P = .000). Long duration of disease, prior interventions, and high MRI-based score were independent risk factors for AF recurrence.The MRI-based score objectively assessed the clinical status and disease activity of patients with AFs, with a high score being associated with severe clinical status and long recovery time.

Potential of vibrational spectroscopy for rapid and accurate determination of the hydrogen peroxide treatment of plant leaves.

Detection and characterization of interactions between crop plants and hydrogen peroxide (H2O2) is significant for the exploration of the mechanisms in plant pathology. The objective of this research is to estimate spectral characteristics of rapeseed leaves (Brassica napus L.) during treatment with different H2O2 concentrations (0, 0.5, 1.0, and 3.0 mmol/L) by using Raman spectroscopy (RS) (800-1800 cm-1) and hyperspectral imaging (HSI) (400-1000 nm). Cluster analysis of RS and HSI data between the control and treated samples was conducted using kernel principal component analysis (KPCA) and principal component analysis (PCA), respectively. Characteristic Raman shifts at 1012, 1163, and 1530 cm-1 and hyperspectral featured wavelengths at 452, 558, 655, and 703 nm were selected for discriminating control and treated samples. The one-way analysis of variance (ANOVA) was applied to demonstrate the significant difference in spectral signatures of samples, and results showed that 452 nm is promising to assess the control and treated samples at the p < 0.05 level. The featured Raman shifts and hyperspectral wavelengths were employed to establish least squares-support vector machine (LS-SVM) discriminative models. The approach of multiple-level data fusion of 1163 cm-1 combined with 452 nm produced the best recognize rate (RR) of 81.7% to detect the control and treated leaves than other models. Therefore, the results encouraged multiple sensor fusion to improve models for better model performance and to detect plant treatment situations with H2O2 solutions.

Clinical study of external application of liuhe dan in the treatment of anal edge edema after mixed hemorrhoid operation.

To observe the therapeutic efficacy of external application of Liuhe Dan in the treatment of anal edge edema after mixed hemorrhoid operation. A total of 160 patients who had been treated for lotion anal edge edema from January 2016 to August 2018 were enrolled research ojbects. They were divided into control group accepting routine nursing methods (80 cases) and research group accepting external application of Liuhe Dan (80 cases). The therapeutic efficacies of two groups were compared. The anal edge edema score and wound pain score of the research group were significantly lower than those of the control group (p<0.05). Meanwhile, the length of hospital stay and wound healing time of the research group were significantly shorter than those of the control group (p<0.05). External application of Liuhe Dan in the treatment of anal edge edema after mixed hemorrhoid operation could significantly improve the therapeutic efficacy and alleviate the patient's pain, which is of great application value.

Segmental resection combined with anoplasty for the treatment of circumferential mixed hemorrhoids.

Circumferential mixed hemorrhoids are very difficult to treat non-surgically. Therefore, it is important to explore the surgical methods for its complete resolution as well as maintenance of normal anal anatomy and function. The present study was designed to evaluate the effect of segmented and plastic hemorrhoidectomy (SPH) on patients with circumferential mixed hemorrhoids. A total of 300 patients with circumferential mixed hemorrhoids were divided into experimental group (n=150) undergoing SPH and control group (n=150) undergoing Milligan-Morgan hemorrhoidectomy. There were no differences in cure and effectiveness rates between two groups. Compared with the control group, patients in the experimental group had shorter healing time (15.7±1.3 vs 12.5±0.7 days) and recovery to normal activity (18.5±2.7 vs 14.7±1.2 days). In addition, anal function of all patients in the experimental group was normal during short- and long-term follow-up. However, more cases in the control group showed anal dampness and itching, and poor control of intestinal liquid. Compared with the control group, patients in the experimental group had better outcomes in overall anal function and smoothness at 6, 12, and 18 months after operation as well as patient satisfaction. Furthermore, the rating in the visual analogue scale for defecation pain and edema in the experimental group was less than that in the control group. SPH was more effective, had fewer complications, better protection of anal function, and a better cosmetic result.

Segmental resection combined with anoplasty for the treatment of circumferential mixed hemorrhoids

Circumferential mixed hemorrhoids are very difficult to treat non-surgically. Therefore, it is important to explore the surgical methods for its complete resolution as well as maintenance of normal anal anatomy and function. The present study was designed to evaluate the effect of segmented and plastic hemorrhoidectomy (SPH) on patients with circumferential mixed hemorrhoids. A total of 300 patients with circumferential mixed hemorrhoids were divided into experimental group (n=150) undergoing SPH and control group (n=150) undergoing Milligan-Morgan hemorrhoidectomy. There were no differences in cure and effectiveness rates between two groups. Compared with the control group, patients in the experimental group had shorter healing time (15.7±1.3 vs 12.5±0.7 days) and recovery to normal activity (18.5±2.7 vs 14.7±1.2 days). In addition, anal function of all patients in the experimental group was normal during short- and long-term follow-up. However, more cases in the control group showed anal dampness and itching, and poor control of intestinal liquid. Compared with the control group, patients in the experimental group had better outcomes in overall anal function and smoothness at 6, 12, and 18 months after operation as well as patient satisfaction. Furthermore, the rating in the visual analogue scale for defecation pain and edema in the experimental group was less than that in the control group. SPH was more effective, had fewer complications, better protection of anal function, and a better cosmetic result.

Enhanced neutrophil autophagy and increased concentrations of IL-6, IL-8, IL-10 and MCP-1 in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a high morbidity and disability disease with numerous inflammatory cells infiltrating in interstitial of articular cartilages and bones. As the most abundant inflammatory cells, neutrophil has been reported that their apoptosis changed gradually in the circumstance of RA. Apoptosis, one modality of programmed cell death (PCD), is closely associated with autophagy, which indicates neutrophil autophagy may also alter in RA. Flow cytometry, western blotting, immunohistochemistry, immunofluorescence, transmission electron microscope and multiplex antibody microarray were used to comparative investigate the status of neutrophil autophagy in patients with RA and in vitro. The results showed that the expression of autophagy related LC3 protein was up-regulated with lower lysosomal pH in neutrophils from synovial fluid of RA and changed under stimulation of CQ and small RNA interferences (siRNAs) Atg5 transfection, which proved in acute promyelocytic leukemia HL-60 cell lines, predominantly a neutrophilic promyelocyte, treated by plasma and synovial fluid from RA. We further found out the concentration of IL-6, IL-8, IL-10 and MCP-1 was higher in their synovial fluid which may mediate neutrophil autophagy in RA via cytokine-cytokine receptor interaction and IL-17 signaling pathway. Our results indicate that neutrophil autophagy may be a novel perspective to understand the pathology which may provide a new maker to diagnose RA and IL-8, IL-10, MCP-1 specific antagonists and neutrophil autophagy target inhibitors may improve the therapeutic effect of RA someday.

Effect of lateral internal sphincterotomy in patients undergoing excisional hemorrhoidectomy.

BACKGROUND: Excisional hemorrhoidectomy (EH) is the major surgical option for high-grade symptomatic hemorrhoids, but it has some shortcomings, especially postoperative pain. This study was performed to assess the effect of lateral internal sphincterotomy (LIS) in patients undergoing excisional hemorrhoidectomy. METHODS: A systematic literature search (Medline, Embase, Cochrane Library, Science Citation Index, Science Direct, Springer Link, Ovid Journals, and EBSCO) was performed to identify all eligible articles. Randomized controlled trials (RCTs) published until July 7, 2017 comparing EH combined with LIS (experimental group) with EH only (control group) were eligible for inclusion. The primary outcome of interest was postoperative pain. RESULTS: Ten RCTs involving 1560 patients were identified for inclusion. The pooled analysis revealed that patients undergoing EH and LIS were associated with lower pain score [standardized mean difference (SMD), -0.75; 95% confidence interval (CI), -1.14 to -0.36; z = 3.76; P = .0002] and resting anal pressure [odds ratio (OR), -17.19; 95% CI, -25.66 to -8.72; z = 3.98; P < .0001], and lower incidence of anal stricture (OR, 0.12; 95% CI, 0.03-0.53; z = 2.85; P = .004). However, the differences of urinary retention, bleeding and length of hospital stay were similar between the 2 methods. CONCLUSION: Our meta-analysis suggests that LIS effectively relieves postoperative pain and reduces patient's postoperative analgesic requirements. LIS also reduces the incidence of anal stenosis but increases the incidence of fecal incontinence.

Development of Noninvasive Classification Methods for Different Roasting Degrees of Coffee Beans Using Hyperspectral Imaging.

This study aimed to develop an approach for quickly and noninvasively differentiating the roasting degrees of coffee beans using hyperspectral imaging (HSI). The qualitative properties of seven roasting degrees of coffee beans (unroasted, light, moderately light, light medium, medium, moderately dark, and dark) were assayed, including moisture, crude fat, trigonelline, chlorogenic acid, and caffeine contents. These properties were influenced greatly by the respective roasting degree. Their hyperspectral images (874⁻1734 nm) were collected using a hyperspectral reflectance imaging system. The spectra of the regions of interest were manually extracted from the HSI images. Then, principal components analysis was employed to compress the spectral data and select the optimal wavelengths based on loading weight analysis. Meanwhile, the random frog (RF) methodology and the successive projections algorithm were also adopted to pick effective wavelengths from the spectral data. Finally, least squares support vector machine (LS-SVM) was utilized to establish discriminative models using spectral reflectance and corresponding labeled classes for each degree of roast sample. The results showed that the LS-SVM model, established by the RF selecting method, with eight wavelengths performed very well, achieving an overall classification accuracy of 90.30%. In conclusion, HSI was illustrated as a potential technique for noninvasively classifying the roasting degrees of coffee beans and might have an important application for the development of nondestructive, real-time, and portable sensors to monitor the roasting process of coffee beans.

[Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film].

In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380～1 030 nm) and NIR (874～1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.

[Discriminate the Rape Sclerotinia at Early Stage Based on Confocal Raman Spectroscopy].

Oilseed rape(Brassica napus L. ) is a principal source of edible oil for human consumption and it feeds livestock as a by product with high energy and protein. However, oilseed plants often suffer from the invasion of various diseases, which could affect the yield and quality of the rapeseeds. Rape sclerotinia rot caused by the fungus sclerotinia sclerotiorum (Lib. ) de Bary may severely affect the growth of oilseed rape. Therefore, searching non-invasive detection methods of detection plant disease at early stage is crucial for monitoring growing conditions of crops. Confocal Raman spectroscopy in the region of 500～2 000 cm(-1) coupled with chemometrics methods were employed to discriminate the rape sclerotinia disease at early stage on the oilseed rape leaves. A total of 60 samples(30 healthy plant leaves and 30 infected leaves) were used to acquire the Raman spectra and wavelet transform was applied to remove the fluorescence background. Regression coefficients of the partial least squares-discriminant analysis(PLS-DA) were used to select the 8 characteristic peaks based on the whole Raman spectra. 983，1 001, 1 205, 1 521, 1 527, 1 658, 1 670 and 1 758 cm(-1) were employed to establish PLS-DA discriminate models and recognition accuracy was 100%. The results showed Raman spectra combined with chemometrics method is promising for detecting rape sclerotinia infection in the oilseed rape leaves at early stage. This study provided a theoretical reference for researching the interaction between the fungus and plants and early detecting of disease infection.