Sensitive Detection of OCS Using Thermal Conversion Combined with Spectral Reconstruction Filtering Differential Optical Absorption Spectroscopy.

Carbonyl sulfide (OCS) is a toxic gas produced during industrial processes that poses risks to both human health and industrial equipment. Therefore, detecting OCS concentrations plays a crucial role in early hazard warning. This paper presents an online system for detecting OCS at the ppb level using thermal conversion and spectral reconstruction filtering differential optical absorption spectroscopy (SRF-DOAS). First, OCS, which is not suitable for DOAS due to its weak absorption characteristics, is completely transformed into SO2 with strong absorption characteristics under high-temperature conditions. Then, the spectral reconstruction filtering method (SRF) is proposed to eliminate the noise and interference. The core idea of the method is to arrange the spectrum according to the spectral intensity from small to large rather than wavelength, reconstructing the spectrum into a new spectrum with linear characteristics. The reconstructed spectrum can remove noise and interference by linear fitting and retain the characteristic of SO2 oscillation absorption. Next, we demonstrate the ability of the reconstructed spectral method to remove noise and interference by comparing the spectra of the inverse-reconstructed gas mixture and SO2. The relative deviation of 0.88% at 100 ppb and detection limit of 7.26 ppb*m for OCS were obtained using the SRF-DOAS method. Finally, the reliability of the system was confirmed by measurements of OCS concentrations in mixture gas of OCS and air, as well as in human exhaled breath.

Immunoglobulin G4 (IgG4) Positive Associated Liver Disease.

BACKGROUND: The goal was to explore the cognition of diagnosis and treatment level of IgG4-related diseases mainly involving lymph nodes. METHODS: The clinical manifestations, laboratory indicators, histopathology, and therapeutic effects of a patient with IgG4-RD suspected of lymphoma were analyzed and the relevant literature was reviewed. RESULTS: Lymph node biopsy showed reactive hyperplasia of lymph node tissue. The liver biochemical indexes were abnormal and the bone marrow smear showed atypical lymphocytes. Lymph node section: IgG4+ cells > 100/HPF (IgG4/IgG > 40%). The serum IgG4 level was 17,200 mg/L, and the diagnosis was IgG4-RD. Oral glucocorticoids took effect after 2 weeks, and no significant enlargement of lymph nodes was observed. CONCLUSIONS: For the diagnosis of IgG4-RD, at present, histopathology is still the gold standard, but a single result cannot diagnose the disease. Comprehensive judgment should be made by combining clinical symptoms, serum IgG4 level and imaging results to prevent misdiagnosis and missed diagnosis, and to avoid over-diagnosis. Short-term hormonal diagnostic therapy may be used in highly suspected patients who cannot be diagnosed. Once diagnosed, standardized medication, adhere to follow-up, regular review, to prevent recurrence and adverse drug reactions.

Luminescence thermometry driven by a support vector machine: a strategy toward precise thermal sensing.

Luminescence thermometry is a promising non-contact temperature measurement technique, but improving the precision and reliability of this method remains a challenge. Herein, we propose a thermal sensing strategy based on a machine learning. By using Gd3Ga5O12: Er3+-Yb3+ as the sensing medium, a support vector machine (SVM) is preliminarily adopted to establish the relationship between temperature and upconversion emission spectra, and the sensing properties are discussed through the comparison with luminescence intensity ratio (LIR) and multiple linear regression (MLR) methods. Within a wide operating temperature range (303-853 K), the maximum and the mean measurement errors actualized by the SVM are just about 0.38 and 0.12 K, respectively, much better than the other two methods (3.75 and 1.37 K for LIR and 1.82 and 0.43 K for MLR). Besides, the luminescence thermometry driven by the SVM presents a high robustness, although the spectral profiles are distorted by the interferences within the testing environment, where, however, LIR and MLR approaches become ineffective. Results demonstrate that the SVM would be a powerful tool to be applied on the luminescence thermometry for achieving a high sensing performance.

Quantitative detection of multicomponent SF6 decomposition products based on Fourier transform infrared spectroscopy combined with SCARS-DNN.

Accurate and efficient quantitative analysis of the decomposition products of the insulating medium SF6 in gas-insulated switchgear (GIS) is important for an effective assessment of its internal insulation status. In this work, a quantitative calibration model of Fourier Transform Infrared Spectroscopy (FTIR) combined with SCARS-DNN (Stability Competitive Adaptive Reweighted Sampling-Deep Neural Network) is proposed for the rapid non-destructive detection of SF6 decomposition products. First, the interference of the background gas SF6 on the absorption spectra of the decomposition products is eliminated according to the Lambert-Beer law, while baseline correction and Savitzky-Golay (S-G) smoothing are used to remove baseline drift and noise. Subsequently, a Monte Carlo cross-validation method is used to detect and eliminate the anomalous samples. Then feature selection is performed using uninformative variable elimination (UVE) and stability competitive adaptive reweighted sampling (SCARS), and finally quantitative calibration models of FULL-DNN (full spectral band), UVE-DNN, and SCARS-DNN are developed. For the quantitative detection of SF6 decomposition products, the SCARS-DNN model had the best prediction performance with a maximum reduction of 96.18% in the root mean square error (RMSE) and 96.11% in the mean absolute percentage error (MAPE). Results reveal that the relative errors are basically kept below 1.36% when predicting the three decomposition products, even in the presence of a high level of SF6 interference. Therefore, the SCARS-DNN model is suitable for high-precision quantitative detection of SF6 decomposition gas.

Different regions and environments have critical roles on yield, main quality and industrialization of an industrial purple-fleshed sweetpotato (Ipomoea batatas L. (Lam.)) "Xuzishu8".

Purple-fleshed sweetpotato (PFSP) (Ipomoea batatas (L.) Lam), whose flesh is purple to dark purple, is a special variety type of sweetpotato, which has the characteristics of food crop, industrial crop and medicinal crop. The storage root (SR) of PFSP is rich in anthocyanins, starch, protein, soluble sugar, mineral elements, polyphenol, dietary fiber and so on, which has balanced and comprehensive nutritional value. And in recent years, its unique nutritional elements are increasingly known for their health functions. At present, there is no article on the characteristics and quality analysis of industrial xz8 variety. To explore the influence of different environments on the processing quality of xz8, we selected nine regions (Xuzhou, Jiawang, Pizhou, Xinyi, Peixian, Sihong, Yanchen, Xiangyang and Tianshui) to measure its yield and quality changes. The data demonstrated that xz8 has a very consistent high yield performance. In Tianshui, the anthocyanins, protein and minerals contents were significantly higher and yield also above average. Moreover, the variety with the lowest starch content exhibited the best taste. On the basis of the above results, it suggested that quite practicable to promote xz8 cultivation and suitable for processing in these areas. Thus, our present findings improve our understanding of xz8 variety and provide the basis for the industrial production of PFSP with strong prospects for success.

Ultrasensitive Online NO Sensor Based on a Distributed Parallel Self-Regulating Neural Network and Ultraviolet Differential Optical Absorption Spectroscopy for Exhaled Breath Diagnosis.

The concentration of fractional exhaled nitric oxide (FeNO) is closely related to human respiratory inflammation, and the detection of its concentration plays a key role in aiding diagnosing inflammatory airway diseases. In this paper, we report a gas sensor system based on a distributed parallel self-regulating neural network (DPSRNN) model combined with ultraviolet differential optical absorption spectroscopy for detecting ppb-level FeNO concentrations. The noise signals in the spectrum are eliminated by discrete wavelet transform. The DPSRNN model is then built based on the separated multipeak characteristic absorption structure of the UV absorption spectrum of NO. Furthermore, a distributed parallel network structure is built based on each absorption feature region, which is given self-regulating weights and finally trained by a unified model structure. The final self-regulating weights obtained by the model indicate that each absorption feature region contributes a different weight to the concentration prediction. Compared with the regular convolutional neural network model structure, the proposed model has better performance by considering the effect of separated characteristic absorptions in the spectrum on the concentration and breaking the habit of bringing the spectrum as a whole into the model training in previous related studies. Lab-based results show that the sensor system can stably achieve high-precision detection of NO (2.59-750.66 ppb) with a mean absolute error of 0.17 ppb and a measurement accuracy of 0.84%, which is the best result to date. More interestingly, the proposed sensor system is capable of achieving high-precision online detection of FeNO, as confirmed by the exhaled breath analysis.

RNA-Sequencing Analysis Revealed Genes Associated with Sweet Potato (Ipomoea batatas (L.) Lam.) Responses to Stem Rot during Different Infection Stages.

The sweet potato, which is an important tuber crop in China, is susceptible to a variety of pathogens and insect pests during cultivation and production. Stem rot is a common sweet potato disease that seriously affects tuber yield and quality. Unfortunately, there have been relatively few studies on the mechanism mediating the stem rot resistance of sweet potatoes. In this study, a transcriptome sequencing analysis was completed using Xushu 48 samples at different stages (T1, T2, and T3) of the stem rot infection. The T1 vs. T2, T1 vs. T3, and T2 vs. T3 comparisons detected 44,839, 81,436, and 61,932 differentially expressed genes (DEGs), respectively. The DEGs encoded proteins primarily involved in alanine, aspartate, and glutamate metabolism (ko00250), carbon fixation in photosynthetic organisms (ko00710), and amino sugar and nucleotide sugar metabolism (ko00520). Furthermore, some candidate genes induced by phytopathogen infections were identified, including gene-encoding receptor-like protein kinases (RLK5 and RLK7), an LRR receptor-like serine/threonine protein kinase (SERK1), and transcription factors (bHLH137, ERF9, MYB73, and NAC053). The results of this study provide genetic insights that are relevant to future explorations of sweet potato stem rot resistance, while also providing the theoretical basis for breeding sweet potato varieties that are resistant to stem rot and other diseases.

Study on temperature effects of broadband absorption spectroscopy based on Doppler broadening combined with a multilinear shape superposition.

In this study, we determine the relationship between the broadband absorption spectroscopy and temperature using Doppler broadening combined with a multilinear shape superposition. First, a method for temperature effects on broadband absorption spectroscopy is proposed, utilizing the principle of a multiple Gaussian line shape superposition. A theoretical expression of the temperature effect on broadband spectroscopy is then presented for the first time to the best of our knowledge, and the variation law of broadband absorption spectroscopy with temperature is explained. Furthermore, the effectiveness of the expression is demonstrated by comparing experimental and theoretical data of the SO2 broadband absorption spectroscopy. The results demonstrate that the correlation coefficient (r) between the experimental and theoretical spectra of SO2 within the temperature range of 298.15-923.15 K is greater than 0.93. The method and expression presented in this Letter can effectively explain the data of previous research.

Comparative Analysis of Saccharification Characteristics of Different Type Sweetpotato Cultivars.

As an important characteristic crop in China, sweetpotato plays an important role in the intake and supplement of nutrients. The saccharification characteristics of sweetpotato determine the edible quality and processing type. Exploring the saccharification characteristics of sweetpotato is of great significance to the selection of processing materials and the formation mechanism of service quality, but there are few relevant studies. A comparison study of two high saccharification varieties (Y25 and Z13) and one low saccharification variety (X27) was conducted to analyze their storage roots physical and chemical properties. The results show that the dry matter content, starch, and amylose content of Y25 and Z13 were significantly different from those of X27. Furthermore, the total amylase activity was significantly higher than that of X27. On the other hand, the starch gelatinization temperature was significantly lower than that of X27. The starch reduction in Y25 and Z13 is four times more than that in X27, and the maltose content of Y25 and Z13 is more than two times that of X27. Finally, the scores of sensory evaluation and physiological sweetness were significantly higher than those of X27. The results provide a theoretical basis for understanding the saccharification characteristics of sweetpotato varieties and are of guiding significance for the selection of sweetpotato parents.

[Clinicopathological Features of Primary Small Cell Neuroendocrine Carcinoma of the Bladder].

Objective To investigate the clinicopathological features,immunohistochemical features,diagnosis,and relationship with sporadic prostate cancer in primary small cell neuroendocrine carcinoma of the bladder. Methods We retrospectively analyzed the clinical characteristics of 12 patients with primary small cell neuroendocrine carcinoma of the bladder diagnosed at Beijing Chao-Yang Hospital affiliated to Capital Medical University from January 2013 to September 2022.The histological features of primary small cell neuroendocrine carcinoma of the bladder were re-evaluated by two pathologists according to the 2022 revision of the World Health Organization Classification of Tumors of the Urinary System and Male Genital Organs.Electronic medical records were retrieved,and telephone follow-up was conducted from the time of histopathological diagnosis to the death or the end of the last follow-up until January 31,2023. Results The 12 patients include 7 patients in pT3 stage and 1 patient in pT4 stage.Eight patients were complicated with other types of tumors,such as high-grade urothelial carcinoma of the bladder and squamous cell carcinoma.Five patients had sporadic prostate cancer.Immunohistochemical staining showed that 12 (100.0%),10 (83.3%),and 8 (66.7%) patients were tested positive for CD56,Syn,and CgA,respectively.The Ki67 proliferation index ranged from 80% to 90%.Five patients with urothelial carcinoma were tested positive for CK20,GATA3,and CK7.P504S was positive in all the 5 patients with prostate cancer,while P63 and 34ßE12 were negative.The follow-up of the 12 patients lasted for 3-60 months.Eight of these patients died during follow-up,with the median survival of 15.5 months.Four patients survived. Conclusions Primary small cell neuroendocrine carcinoma of the bladder is a rare urological tumor with high aggressiveness and poor prognosis.In male patients with bladder prostatectomy,all prostate tissue should be sampled.If prostate cancer is detected,the prostate-specific antigen level should be monitored.

Identification and functional characterization of a flavonol synthase gene from sweet potato [Ipomoea batatas (L.) Lam.].

Flavonol synthase (FLS) is a key enzyme of the flavonoid biosynthetic pathway, which catalyzes the conversion of dihydroflavonols into flavonols. In this study, the FLS gene IbFLS1 was cloned and characterized from sweet potato. The resulting IbFLS1 protein showed a high similarity with other plant FLSs. The conserved amino acids (HxDxnH motifs) binding ferrous iron and residues (RxS motifs) binding 2-oxoglutarate were found in IbFLS1 at conserved positions, as in other FLSs, suggesting that IbFLS1 belongs to the 2-oxoglutarate-dependent dioxygenases (2-ODD) superfamily. qRT-PCR analysis showed an organ-specific pattern of expression of the IbFLS1 gene, which was predominantly expressed in young leaves. The recombinant IbFLS1 protein could catalyze the conversion of dihydrokaempferol and dihydroquercetin to kaempferol and quercetin, respectively. The results of subcellular localization studies indicated that IbFLS1 was found mainly in the nucleus and cytomembrane. Furthermore, silencing the IbFLS gene in sweet potato changed the color of the leaves to purple, substantially inhibiting the expression of IbFLS1 and upregulating the expression of genes involved in the downstream pathway of anthocyanin biosynthesis (i.e., DFR, ANS, and UFGT). The total anthocyanin content in the leaves of the transgenic plants was dramatically increased, whereas the total flavonol content was significantly reduced. Thus, we conclude that IbFLS1 is involved in the flavonol biosynthetic pathway and is a potential candidate gene of color modification in sweet potato.

A Case of Acute Mixed Cell Leukemia Resembling AML1-ETO Positive Acute Myeloid Leukemia.

BACKGROUND: The aim of the study was to improve the understanding of complex karyotype acute mixed cell leukemia containing pseudo Chediak-Higashi granules. METHODS: A case of acute mixed cell leukemia resembling AML1-ETO positive acute myeloid leukemia was reported. The results of morphological, immunophenotypic, and cytogenetic tests were analyzed by reviewing relevant literature. RESULTS: The patient was a young boy with clinical manifestations of recurrent fever. Bone marrow smear: Granulocyte system hyperplasia is obvious, visible at each stage, primitive cells account for 12%. These cells are large in volume, mostly round or class round, with abundant cell mass, stained gray blue, unbalanced development of some nuclear plasma, abnormal cytoplasmic staining, and visible "sunrise red" -like changes. Typical Auer bodies, pseudo Chadiak-Higashi granules and phagocytic erythroid substances were observed. The nuclei are irregular in shape, distorted and depressed, with fine chromatin and prominent large nucleoli. Bone marrow was extracted 3 days later, the bone marrow smear showed 65% primitive cells. The morphology of primitive cells was similar to that of 3 days ago. The results of flow cytometry showed that the primary/naive T cells in the samples possessed nuclear cells. Flow cytometry showed two groups of abnormal cells. One group accounted for 3.87% of nuclear cells and was a primitive/naive T-cell phenotype, mainly expressing: CD34+, CD7+, CD5+, CD2dim+, MPO-, CCD3 + part, CD3-, CD4-, CD8 -, CD117 -, CD13-, CD33-, HLA - DR -, CD10-, CD11b-, CD56-. The other group which accounted for 79.8% of the nuclear cells was monocyte phenotype, mainly expressing: CD34-, CD117-, CD13+ small amount, CD33+, HLA-DR-, CD11b+, CD14+, CD15+, CD36+, CD56+, CD64+, CD4+, CD85J+, CD85K + part. It matched the immunophenotype of acute mixed cell leukemia (T/MMPAL). Immunophenotypic leukemia-related fusion genes were negative, and karyotype analysis results were 45, XY, T (11; 12)(p13; Q13), -12-17, + mar [12]/90 < n > 4, idem x 2 [6]/46, XY. Combined with the above results, acute mixed cell leukemia was diagnosed. CONCLUSIONS: The flow cytometry is the gold standard in the diagnosis of acute mixed cell leukemia. The diagnosis of acute mixed cell leukemia requires the combination of clinical manifestations, cellular morphology, immunology, cytogenetics and molecular biology, and the comprehensive diagnosis efficiency is obviously better than that of morphology.

A survey on image enhancement for Low-light images.

In real scenes, due to the problems of low light and unsuitable views, the images often exhibit a variety of degradations, such as low contrast, color distortion, and noise. These degradations affect not only visual effects but also computer vision tasks. This paper focuses on the combination of traditional algorithms and machine learning algorithms in the field of image enhancement. The traditional methods, including their principles and improvements, are introduced from three categories: gray level transformation, histogram equalization, and Retinex methods. Machine learning based algorithms are not only divided into end-to-end learning and unpaired learning, but also concluded to decomposition-based learning and fusion based learning based on the applied image processing strategies. Finally, the involved methods are comprehensively compared by multiple image quality assessment methods, including mean square error, natural image quality evaluator, structural similarity, peak signal to noise ratio, etc.

An adaptive absorption spectroscopy with adjustable moving window width for suppressing nonlinear effects in absorbance measurements.

Absorption spectroscopy based on Lambert-Beer law has been widely used in material structure analysis, research in chemical reaction kinetics, and exploration of various physicochemical reaction mechanisms. However, serious nonlinearity between absorbance and measured concentration can occur in actual measurements. The idea of moving window is first introduced into the field of spectral nonlinearity in the paper. Combining with the characteristic absorption spectra of the substances to be measured, we propose an adaptive absorption spectroscopy (A-AS) with adjustable moving window parameters to effectively suppress the nonlinear effects in absorbance measurements. The validity of this method is verified by taking the differential optical absorption spectroscopy to detect SO2 as an example. The 210-230 nm characteristic absorption band is traversed and divided by the moving window with adjustable parameters, and the estimated coefficient (k-value) of each band is calculated. On this basis, all k-values are initially and secondly screened to obtain the optimal kbest, and then the optimal concentration value is obtained by inversion. Compared with the broad-band method and narrow-band method, it shows excellent performance that the maximum error and standard deviation of A-AS is only 1.3% and 3.8 in the entire concentration range, suggesting good linearity and stability in both high and low concentration environments. Therefore, it is inferred that A-AS is universally adaptable and enables dynamic linear measurements over wide concentration range.

Expression pattern of peritoneum IL-6 is associated with baseline peritoneal transport function in uremic patients before dialysis.

OBJECTIVE: This study aimed to investigate the biological factors associated with baseline peritoneal transport in uremic patients before dialysis. METHODS: Thirty patients with uremia were grouped according to their peritoneal dialysate creatinine/serum creatinine ratio (D/P) as high-transport (H, 16 cases) with D/P>0.65 and low-transport (L, 14 cases) with D/P≤0.65 one month after continuous ambulatory peritoneal dialysis treatment. Multi-inflammatory levels such as serum IL-6 and albumin, peritoneal IL-6 level, and microvessel density (MVD) of visceral peritoneal were compared and correlated between the two groups to determine the associated factors. RESULTS: There were no significant differences in clinical parameters between the two groups (p < 0.05). There were no significant differences in serum IL-6 and albumin between the two groups. However, peritoneal IL-6 and MVD in group H were significantly higher than group L (p=0.012, p=0.044), and they were positively correlated (r=0.368, p=0.045). Furthermore, baseline D/P was positively correlated with IL-6 expressions (r=0.640, p=0.000) and peritoneal MVD (r=0.476, p=0.008), and independently associated with peritoneal IL-6 expression (p=0.004). CONCLUSIONS: The baseline peritoneal transport performance is associated with peritoneal IL-6 expression and MVD but not circulatory IL-6.

Genome-Wide Identification of the A20/AN1 Zinc Finger Protein Family Genes in Ipomoea batatas and Its Two Relatives and Function Analysis of IbSAP16 in Salinity Tolerance.

Stress-associated protein (SAP) genes-encoding A20/AN1 zinc-finger domain-containing proteins-play pivotal roles in regulating stress responses, growth, and development in plants. They are considered suitable candidates to improve abiotic stress tolerance in plants. However, the SAP gene family in sweetpotato (Ipomoea batatas) and its relatives is yet to be investigated. In this study, 20 SAPs in sweetpotato, and 23 and 26 SAPs in its wild diploid relatives Ipomoea triloba and Ipomoea trifida were identified. The chromosome locations, gene structures, protein physiological properties, conserved domains, and phylogenetic relationships of these SAPs were analyzed systematically. Binding motif analysis of IbSAPs indicated that hormone and stress responsive cis-acting elements were distributed in their promoters. RT-qPCR or RNA-seq data revealed that the expression patterns of IbSAP, ItbSAP, and ItfSAP genes varied in different organs and responded to salinity, drought, or ABA (abscisic acid) treatments differently. Moreover, we found that IbSAP16 driven by the 35 S promoter conferred salinity tolerance in transgenic Arabidopsis. These results provided a genome-wide characterization of SAP genes in sweetpotato and its two relatives and suggested that IbSAP16 is involved in salinity stress responses. Our research laid the groundwork for studying SAP-mediated stress response mechanisms in sweetpotato.

A C2-Domain Abscisic Acid-Related Gene, IbCAR1, Positively Enhances Salt Tolerance in Sweet Potato (Ipomoea batatas (L.) Lam.).

Plant C2-domain abscisic acid-related (CAR) protein family plays an important role in plant growth, abiotic stress responses, and defense regulation. In this study, we cloned the IbCAR1 by homologous cloning method from the transcriptomic data of Xuzishu8, which is a sweet potato cultivar with dark-purple flesh. This gene was expressed in all tissues of sweet potato, with the highest expression level in leaf tissue, and it could be induced by NaCl and ABA. Subcellular localization analyses indicated that IbCAR1 was localized in the nucleus and plasma membrane. The PI staining experiment revealed the distinctive root cell membrane integrity of overexpressed transgenic lines upon salt stress. Salt stress significantly increased the contents of proline, ABA, and the activity of superoxide dismutase (SOD), whereas the content of malondialdehyde (MDA) was decreased in overexpressed lines. On the contrary, RNA interference plants showed sensitivity to salt stress. Overexpression of IbCAR1 in sweet potatoes could improve the salt tolerance of plants, while the RNAi of IbCAR1 significantly increased sensitivity to salt stress in sweet potatoes. Meanwhile, the genes involved in ABA biosynthesis, stress response, and reactive oxygen species (ROS)-scavenging system were upregulated in overexpressed lines under salt stress. Taken together, these results demonstrated that IbCAR1 plays a positive role in salt tolerance by relying on the ABA signal transduction pathway, activating the ROS-scavenging system in sweet potatoes.

Evaluation of Physiological Coping Strategies and Quality Substances in Purple SweetPotato under Different Salinity Levels.

Although salinity stress is one of the principal abiotic stresses affecting crop yield, a suitable concentration of NaCl has proven to be useful for increasing crop quality. This study used low salinity (34 mmol/L NaCl) and high salinity (85 mmol/L) to cultivate purple sweetpotato. Using transcriptomics and metabolomics to profile the pathway indicated that glycometabolism, secondary metabolite biosynthesis and the starch catabolic process were the significant pathways under the salinity stress. Further research showed that purple sweetpotato could regulate genes related to the regulation of the cellular Na+, K+, and other ions concentration in response to the low salinity tolerance, but loses this ability under high salinity. Meanwhile, under low salinity, the activity of antioxidant enzymes and their related gene expression are maintained at a high level. The low salinity influences the monosaccharide composition as well as the content and regulation of genes related to starch synthesis. Quality analysis showed that the low salinity could increase the starch content and influence the amylopectin biosynthesis. It suggested that low salinity promotes substance accumulation. High salinity could increase the anthocyanins biosynthesis and low salinity had a significant impact on phenolic acid and flavonol. Finally, the gene expression levels also prove the low salinity could change the composition and content level of the purple sweetpotato. This study showed that an appropriate concentration of NaCl can be used as an elicitor for application in purple sweetpotato planting.

Highly sensitive trace oxygen sensing based on far-ultraviolet absorption spectroscopy.

High-sensitivity trace oxygen sensing based on far-ultraviolet absorption spectroscopy was realized. The far-ultraviolet absorption spectrum of oxygen in the wavelength range of 170-200 nm at normal pressure was measured, and the maximum oscillation absorption peak occurred close to 180.18 nm. Through error analysis, the optimal wavelength range for accurate and sensitive oxygen measurements by ultraviolet absorption spectroscopy was identified as 180-189 nm. A total column (CL) calibration curve for oxygen was established, and the maximum optical path length (L1) of the system was determined to be 0.75(3) m by comparing the oxygen absorption with and without the sample cell. The oxygen detection sensitivity was 232 m-1, and the lowest detection limit was 12 ppm at the L1 optical path length. The highly sensitive trace oxygen sensing based on far-ultraviolet absorption spectroscopy exhibited significant potential for application with regard to nitrogen protection.

Comparative Transcriptome Profiling Reveals the Genes Involved in Storage Root Expansion in Sweetpotato (Ipomoea batatas (L.) Lam.).

Sweetpotato (Ipomoea batatas (L.) Lam.) is recognized as one of the most important root crops in the world by the Food and Agriculture Organization of the United Nations. The yield of sweetpotato is closely correlated with the rate of storage root (SR) formation and expansion. At present, most of the studies on sweetpotato SR expansion are focused on the physiological mechanism. To explore the SR expansion mechanism of sweetpotato, we performed transcriptome sequencing of SR harvested at 60, 90, 120, and 150 days after planting (DAP) to analyze two sweetpotato lines, Xuzishu 8 and its crossing progenies named Xu 18-192, which were selected from an F1 segregation population of Xuzishu 8 and Meiguohong, in which SR expansion was delayed significantly. A total of 57,043 genes were produced using transcriptome sequencing, of which 1312 were differentially expressed genes (DEGs) in four SR growth periods of the sweetpotato lines. The combination of the KEGG and trend analysis revealed several key candidate genes involved in SR expansion. The SBEI gene involved in starch metabolism, and transcription factors ARF6, NF-YB3 and NF-YB10 were all significantly up-regulated during SR expansion. The data from this study provide insights into the complex mechanisms of SR formation and expansion in sweetpotato and identify new candidate genes for increasing the yield of sweetpotato.