High-Precision Intelligent Cancer Diagnosis Method: 2D Raman Figures Combined with Deep Learning.

Raman spectroscopy, as a label-free detection technology, has been widely used in tumor diagnosis. However, most tumor diagnosis procedures utilize multivariate statistical analysis methods for classification, which poses a major bottleneck toward achieving high accuracy. Here, we propose a concept called the two-dimensional (2D) Raman figure combined with convolutional neural network (CNN) to improve the accuracy. Two-dimensional Raman figures can be obtained from four transformation methods: spectral recurrence plot (SRP), spectral Gramian angular field (SGAF), spectral short-time Fourier transform (SSTFT), and spectral Markov transition field (SMTF). Two-dimensional CNN models all yield more than 95% accuracy, which is higher than the PCA-LDA method and the Raman-spectrum-CNN method, indicating that 2D Raman figure inputs combined with CNN may be one reason for gaining excellent performances. Among 2D-CNN models, the main difference is the conversion, where SRP is based on the structure of wavenumber series with the best performances (98.9% accuracy, 99.5% sensitivity, 98.3% specificity), followed by SGAF on the wavenumber series, SSTFT on wavenumber and intensity information, and SMTF on wavenumber position information. The inclusion of external information in the conversion may be another reason for improvement in the accuracy. The excellent capability shows huge potential for tumor diagnosis via 2D Raman figures and may be applied in other spectroscopy analytical fields.

LncRNA Expression Profiling in Advanced Resected Gastric Adenocarcinoma Tissues.

BACKGROUND: Long noncoding RNAs (lncRNAs) are the chief products of human transcriptomes and have a major function in mediating gene expression. Abnormal lncRNA levels have been detected in gastric cancer. However, changes in lncRNA expression in advanced gastric adenocarcinoma (GA) are largely unexplored. METHODS: We studied the expression of lncRNAs and mRNAs in 6 advanced resected GA (ARGA) tissues using a lncRNA microarray chip. RESULTS: Among 22,870 lncRNAs expressed in ARGA and paired nonneoplastic tissues (non-GA), 1,769 and 1,710 were up- or downregulated, respectively, in all 6 ARGA tissues (≥ 2.0-fold, p < 0.05). The expression of 5 differentially expressed lncRNAs, HNF1A-AS1, RP11-62F24.2, GAS5, MALAT1, and H19 were randomly selected to be measured in 47 patients using real-time quantitative reverse transcription PCR (qRT-PCR), and the data were consistent with those obtained from the microarray chip. Analysis of their nearby coding genes (mRNAs) revealed that the main associated GO (gene ontology) classes were genes that regulate cellular metabolic processes, protein binding and receptor binding, whereas the main associated pathways were MAPK signaling, which regulates cell proliferation and differentiation and the apoptosis pathway, which is cancer-related. Some (n = 37) differentially expressed lncRNAs had direct annotated functions; among these lncRNAs, 27 were associated with cancer, cancer pathways, oncogenes, and tumor suppressor genes and with cell development and differentiation. CONCLUSIONS: Expression differences in lncRNAs exist between advanced GA and noncancerous gastric tissues, so lncRNA expression patterns may explain gastric carcinogenesis and progression as well as serve as candidate biomarkers for the treatment of GA.

Influence of pancreaticoduodenectomy for periampullary carcinoma on intestinal microbiome and metabolites.

Recent growing evidence suggests a role for intestinal microbiome and metabolites in patients' postoperative recovery. Therefore, there is a need to gain insight into the impact of pancreaticoduodenectomy for periampullary carcinoma on microbiome and metabolites and the potential impact of their changes on patients' condition. Based on 16S rDNA gene sequencing and untargeted metabolomic analysis, we found that the diversity and abundance of intestinal microbiome were significantly higher in patients preoperatively than postoperatively, and the level of intestinal probiotics was significantly lower after surgery compared with preoperatively. In addition, the choline metabolism level was increased and the amino acid metabolism level was decreased after surgery. A total of 53 differential microbiome and 52 differential metabolites were detected, and the differential metabolites were mapped to approximately 60 different KEGG metabolic pathways, of which 13 KEGG metabolic pathways had a differential metabolite number greater than 5. A total of 88 colony-metabolite pairs with significant positive correlation and 69 colony-metabolite pairs with significant negative correlation were identified. Our results reveal alterations in intestinal microbiome after pancreaticoduodenectomy, suggesting its association with postoperative complications. Moreover, the elevated choline metabolism level in postoperative patients may predict their poorer prognosis. At the same time, the decreased abundance of such probiotic bacteria as Prevotella spp. in the postoperative intestine of patients will affect the amino acid metabolism of the organism to some extent.

Transient stimulated Raman scattering spectroscopy and imaging.

Stimulated Raman scattering (SRS) has been developed as an essential quantitative contrast for chemical imaging in recent years. However, while spectral lines near the natural linewidth limit can be routinely achieved by state-of-the-art spontaneous Raman microscopes, spectral broadening is inevitable for current mainstream SRS imaging methods. This is because those SRS signals are all measured in the frequency domain. There is a compromise between sensitivity and spectral resolution: as the nonlinear process benefits from pulsed excitations, the fundamental time-energy uncertainty limits the spectral resolution. Besides, the spectral range and acquisition speed are mutually restricted. Here we report transient stimulated Raman scattering (T-SRS), an alternative time-domain strategy that bypasses all these fundamental conjugations. T-SRS is achieved by quantum coherence manipulation: we encode the vibrational oscillations in the stimulated Raman loss (SRL) signal by femtosecond pulse-pair sequence excited vibrational wave packet interference. The Raman spectrum was then achieved by Fourier transform of the time-domain SRL signal. Since all Raman modes are impulsively and simultaneously excited, T-SRS features the natural-linewidth-limit spectral line shapes, laser-bandwidth-determined spectral range, and improved sensitivity. With ~150-fs laser pulses, we boost the sensitivity of typical Raman modes to the sub-mM level. With all-plane-mirror high-speed time-delay scanning, we further demonstrated hyperspectral SRS imaging of live-cell metabolism and high-density multiplexed imaging with the natural-linewidth-limit spectral resolution. T-SRS shall find valuable applications for advanced Raman imaging.

Periumbilical giant abscess and intestinal leakage in late pregnancy: A rare case report and literature review.

BACKGROUND: Complicated Periumbilical abscess in late pregnancy is rare in clinical practice. Pubmed searches for articles published from January 1980 to September 2021. Such related reports did not retrieve article about "pregnancy" and "periumbilical abscess." CASE PRESENTATION: We reported on a 34-year-old female patient who was admitted to the hospital with periumbilical pain for 3 days at 34 + 1 weeks of pregnancy. The result of imaging examination showed that there was an inflammatory mass in the middle and lower abdominal wall in the third trimester of pregnancy. The periumbilical abscess was punctured and drained first, and then the pregnant woman was assisted to give birth to a baby girl through vagina after the condition was stable.Subsequently, laparotomy + abdominal abscess resection and drainage + partial small bowel resection + ileostomy were performed. Pathology showed inflammatory mass. CONCLUSIONS: Periumbilical abscess in the third trimester of pregnancy is rare clinically. For some pregnant women with previous trauma and surgical history, obstetric examination should not be restricted. For example, pregnant women with a history of abdominal surgery should expand the range of abdominal color Doppler ultrasound during the prenatal examination. When necessary, combine with computed tomography for diagnosis and treatment, avoid missed diagnosis, which will make the treatment more difficult and increase the risk. If the pregnant women has corresponding symptoms in the third trimester, vaginal delivery can be performed to terminate the pregnancy, and then the periumbilical abscess can be removed. At the same time, closely monitor the vital signs of newborn and mothers.

Cubosomes-assisted transdermal delivery of doxorubicin and indocyanine green for chemo-photothermal combination therapy of melanoma.

Melanoma is a highly aggressive form of skin cancer with limited therapeutic options. Chemo-photothermal combination therapy has demonstrated potential for effectively treating melanoma, and transdermal administration is considered the optimal route for treating skin diseases due to its ability to bypass first-pass metabolism and enhance drug concentration. However, the stratum corneum presents a formidable challenge as a significant barrier to drug penetration in transdermal drug delivery. Lipid-nanocarriers, particularly cubosomes, have been demonstrated to possess significant potential in augmenting drug permeation across the stratum corneum. Herein, cubosomes co-loaded with doxorubicin (DOX, a chemotherapeutic drug) and indocyanine green (ICG, a photothermal agent) (DOX-ICG-cubo) transdermal drug delivery system was developed to enhance the therapeutic efficiency of melanoma by improving drug permeation. The DOX-ICG-cubo showed high encapsulation efficiency of both DOX and ICG, and exhibited good stability under physiological conditions. In addition, the unique cubic structure of the DOX-ICG-cubo was confirmed through transmission electron microscopy (TEM) images, polarizing microscopy, and small angle X-ray scattering (SAXS). The DOX-ICG-cubo presented high photothermal conversion efficiency, as well as pH and thermo-responsive DOX release. Notably, the DOX-ICG-cubo exhibited enhanced drug permeation efficiency, good biocompatibility, and improved in vivo anti-melanoma efficacy through the synergistic effects of chemo-photothermal therapy. In conclusion, DOX-ICG-cubo presented a promising strategy for melanoma treatment.

Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning.

Intraoperative detection of the marginal tissues is the last and most important step to complete the resection of adenocarcinoma and squamous cell carcinoma. However, the current intraoperative diagnosis is time-consuming and requires numerous steps including staining. In this paper, we present the use of Raman spectroscopy with deep learning to achieve accurate diagnosis with stain-free process. To make the spectrum more suitable for deep learning, we utilize an unusual way of thinking which regards Raman spectral signal as a sequence and then converts it into two-dimensional Raman spectrogram by short-time Fourier transform as input. The normal-adenocarcinoma deep learning model and normal-squamous carcinoma deep learning model both achieve more than 96% accuracy, 95% sensitivity and 98% specificity when test, which higher than the conventional principal components analysis-linear discriminant analysis method with normal-adenocarcinoma model (0.896 accuracy, 0.867 sensitivity, 0.926 specificity) and normal-squamous carcinoma model (0.821 accuracy, 0.776 sensitivity, 1.000 specificity). The high performance of deep learning models provides a reliable way for intraoperative detection of marginal tissue, and is expected to reduce the detection time and save human lives.

Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.

Multivariate statistical analysis methods have an important role in spectrochemical analyses to rapidly identify and diagnose cancer and the subtype. However, utilizing these methods to analyze lager amount spectral data is challenging, and poses a major bottleneck toward achieving high accuracy. Here, a new convolutional neural networks (CNN) method based on short-time Fourier transform (STFT) to diagnose lung tissues via Raman spectra readily is proposed. The models yield that the accuracies of the new method are higher than the conventional methods (principal components analysis -linear discriminant analysis and support vector machine) for validation group (95.2% vs 85.5%, 94.4%) and test group (96.5% vs 90.4%, 93.9%) after cross-validation. The results illustrate that the new method which converts one-dimensional Raman data into two-dimensional Raman spectrograms improve the discriminatory ability of lung tissues and can achieve automatically accurate diagnosis of lung tissues.

A dicentric chromosome identification method based on clustering and watershed algorithm.

Aiming at the problem of low efficiency of dicentric chromosome identification counting under the microscope, this paper presents a joint processing algorithm combining clustering and watershed. The method first uses clustering and watershed algorithm to segment the original chromosome image, and then identifies the individual chromosomes. The results show that when the equivalent width Y parameter is selected m = 1, n = 1, the true positive rate of dicentric chromosome identification is 76.6%, and positive predictive value is 76.6% in high dose, which is higher than the threshold algorithm for the true positive rate (63.9%) and positive predictive value (63.5%). The number of identified dicentric chromosomes can be used for dose estimation. When 500 cells are used for identification and dose estimation, the dose estimation pass rate can reach 80% in high dose. But for low dose, more cells should be used to identify to increase the dose estimation pass rate.

Desorption behavior of methylene blue on pyromellitic dianhydride modified biosorbent by a novel eluent: acid TiO2 hydrosol.

In this study, waste beer yeast powder was modified by pyromellitic dianhydride to improve its adsorption capacities for cationic dye: methylene blue (MB). According to the Langmuir equation, the maximum uptake capacities (q(m)) of the modified biomass for MB was 830.8 mg g(-1), which was about five times than that obtained on the unmodified biomass. Adsorption mechanism was investigated by FTIR. Desorption kinetics of methylene blue in six solvents: HCl (0.1 mol L(-1)), ethanol, mixtures of HCl (0.1 mol L(-1)) and ethanol with different volume ratio and a self-clean eluent: acid TiO(2) were studied in details. Results showed that desorption kinetics curve fit the two-step kinetic model, and methylene blue release process was distinctly divided into two steps: rapid and slow desorption steps. 52.2% of the methylene blue could be desorbed into TiO(2) hydrosol after 30 h desorption at the first desorption cycle, and the desorbed dye in TiO(2) hydrosol could be degrade completely under sunlight irradiation. After three desorption-photodegradation cycles, 80.0% of the absorbed dyes could be desorbed from the surface of the modified biomass. Although there was much work to do, the self-clean eluent: TiO(2) hydrosol had great potential in practical use.