Visualization of laser-induced breakdown spectroscopy data of mouse organs based on the feature extraction method.

At present, there is no comprehensive and systematic research on laser-induced breakdown spectroscopy (LIBS) data visualization. In particular, the LIBS spectra of biological samples have large noise and weak signals, which seriously affect the feature visualization. Here, three commonly used sample visualization methods were compared, and a new method was applied for tissue sample visualization. We used the LIBS mapping technique to obtain LIBS spectra of different organ slice samples from mice. LIBS spectral distribution was visualized after extracting the region of interest. The three spectral visualization methods are compared, and the performance of visualization algorithms is quantitatively analyzed. The potential of heat-diffusion for the affinity-based transition embedding (PHATE) method highlights the details of the LIBS spectral distribution while maintaining the overall structure of the data. The correlation coefficient between dimensionality reduction data and raw data is 0.97, and the average distance between samples of different categories is 0.64, which are superior to those of traditional principal component analysis (PCA), multidimensional scaling (MDS), and t-distributed stochastic neighbor embedding (t-SNE). The results show that the PHATE method can serve as a very promising LIBS spectral visualization tool.

Cycle-level traffic conflict prediction at signalized intersections with LiDAR data and Bayesian deep learning.

Real-time safety prediction models are vital in proactive road safety management strategies. This study develops models to predict traffic conflicts at signalized intersections at the signal cycle level, using advanced Bayesian deep learning techniques and efficient LiDAR points. The modeling framework contains three phases, which are data preprocessing, base deep learning model development, and Bayesian deep learning model development. The core of the framework is the long short-term memory (LSTM) employed to predict the conflict frequency of a cycle by using traffic features of the previous five cycles (e.g., dynamic traffic parameters, traffic conflict frequency). Four Bayesian deep learning models were developed, including Bayesian-Standard LSTM, Bayesian-Hybrid-LSTM, Bayesian-Stacked-LSTM Encoder-Decoder, and Bayesian-Multi-head Stacked-LSTM Encoder-Decoder. The developed models were applied to traffic conflicts extracted from LiDAR points that were collected from a signalized intersection in Harbin, China with a total duration of seven days. Traffic conflicts, measured by the modified time-to-collision conflict indicator, were identified using the peak over threshold approach. The models were thoroughly evaluated from the aspects of reliability, transferability, sensitivity, and robustness. The results show that the developed four models can predict traffic conflict frequency per cycle per lane simultaneously with its uncertainty. Moreover, the two Bayesian encoder-decoder models perform better than Bayesian-Standard LSTM and Bayesian-Hybrid-LSTM in the four tests. Bayesian-Multi-head Stacked-LSTM Encoder-Decoder is suggested as the optimal model for its high reliability under uncertainty, good transferability in three scenarios, low sensitivity to different parameters, and sound robustness against small noise. The proposed framework could benefit studies on the state-of-the-art data-driven approach for real-time safety prediction.

α-ionone promotes keratinocyte functions and accelerates epidermal barrier recovery.

Background: As a common fragrance ingredient, α-ionone is widely used in cosmetics, perfume, and hygiene products. Nevertheless, little information is available for its biological activities on the skin. In this study, we investigated the effect of α-ionone on keratinocyte functions associated with skin barrier repair and further evaluated its skin barrier recovery capacity to explore its therapeutic potential for the treatment of skin barrier disruption. Methods: The effect of α-ionone on the keratinocyte functions including cell proliferation, migration, and production of hyaluronic acid (HA) and human ß-defensin-2 (HBD-2) were examined in vitro using human immortalized keratinocytes (HaCaT cells) as experimental model. The barrier recovery effects of topical hydrogels containing 0.1% or 1% α-ionone were tested on the volar forearm of 31 healthy volunteers by measuring transepidermal water loss (TEWL) and stratum corneum (SC) hydration following barrier disruption induced by repeated tape-stripping. The statistical significance was evaluated by one-way analysis of variance (ANOVA) followed by a Dunnett's post-hoc test. Results: α-ionone promoted HaCaT cell proliferation (P<0.01) dose-dependently in the 10 to 50 µM range. Meanwhile, it also increased the intracellular cyclic adenosine monophosphate (cAMP) levels (P<0.05). Furthermore, HaCaT cells treated with α-ionone (10, 25, 50 µM) showed enhanced cell migration (P<0.05), up-regulated gene expression of hyaluronic acid synthases 2 (HAS2) (P<0.05), HAS3 (P<0.01), and HBD-2 (P<0.05), and enhanced production of HA (P<0.01) and HBD-2 (P<0.05) in the culture supernatant. These beneficial actions of α-ionone were abrogated by cAMP inhibitor, suggesting that its effects are cAMP-mediated in HaCaT cells. In vivo study showed that topical application of α-ionone-containing hydrogels accelerated the epidermal barrier recovery of human skin after barrier disruption by tape stripping. Treatment with hydrogel containing 1% α-ionone resulted in a significant increase of above 15% in the barrier recovery rate at day 7 post-treatment when compared to the vehicle control (P<0.01). Conclusions: These results demonstrated the role of α-ionone in the improvement of keratinocyte functions and the epidermal barrier recovery. These findings suggest possible therapeutic application of α-ionone in the treatment of skin barrier disruption.

Role of Omega-Hydroxy Ceramides in Epidermis: Biosynthesis, Barrier Integrity and Analyzing Method.

Attached to the outer surface of the corneocyte lipid envelope (CLE), omega-hydroxy ceramides (ω-OH-Cer) link to involucrin and function as lipid components of the stratum corneum (SC). The integrity of the skin barrier is highly dependent on the lipid components of SC, especially on ω-OH-Cer. Synthetic ω-OH-Cer supplementation has been utilized in clinical practice for epidermal barrier injury and related surgeries. However, the mechanism discussion and analyzing methods are not keeping pace with its clinical application. Though mass spectrometry (MS) is the primary choice for biomolecular analysis, method modifications for ω-OH-Cer identification are lacking in progress. Therefore, finding conclusions on ω-OH-Cer biological function, as well as on its identification, means it is vital to remind further researchers of how the following work should be done. This review summarizes the important role of ω-OH-Cer in epidermal barrier functions and the forming mechanism of ω-OH-Cer. Recent identification methods for ω-OH-Cer are also discussed, which could provide new inspirations for study on both ω-OH-Cer and skin care development.

Protective effect of Saussurea involucrata polysaccharide against skin dryness induced by ultraviolet radiation.

Background: Exposure to ultraviolet B (UVB) radiation can damage the epidermis barrier function and eventually result in skin dryness. At present, little work is being devoted to skin dryness. Searching for active ingredients that can protect the skin against UVB-induced dryness will have scientific significance. Methods: Saussurea involucrata polysaccharide (SIP) has been shown to have significant antioxidant and anti-photodamage effects on the skin following UVB irradiation. To evaluate the effect of SIP on UVB-induced skin dryness ex vivo, SIP-containing hydrogel was applied in a mouse model following exposure to UVB and the levels of histopathological changes, DNA damage, inflammation, keratinocyte differentiation, lipid content were then evaluated. The underlying mechanisms of SIP to protect the cells against UVB induced-dryness were determined in HaCaT cells. Results: SIP was found to lower UVB-induced oxidative stress and DNA damage while increasing keratinocyte differentiation and lipid production. Western blot analysis of UVB-irradiated skin tissue revealed a significant increase in peroxisome proliferator-activated receptor-α (PPAR-α) levels, indicating that the underlying mechanism may be related to PPAR-α signaling pathway activation. Conclusions: By activating the PPAR-α pathway, SIP could alleviate UVB-induced oxidative stress and inhibit the inflammatory response, regulate proliferation and differentiation of keratinocytes, and mitigate lipid synthesis disorder. These findings could provide candidate active ingredients with relatively clear mechanistic actions for the development of skin sunscreen moisturizers.

Individual Micron-Sized Aerosol Qualitative Analysis-Combined Raman Spectroscopy and Laser-Induced Breakdown Spectroscopy by Optical Trapping in Air.

The attribution of single particle sources of atmospheric aerosols is an essential problem in the study of air pollution. However, it is still difficult to qualitatively analyze the source of a single aerosol particle using noncontact in situ techniques. Hence, we proposed using optical trapping to combine gated Raman spectroscopy with laser-induced breakdown spectroscopy (LIBS) in a single levitated micron aerosol. The findings of the spectroscopic imaging indicated that the particle plasma formed by a single particle ablation with a pulsed laser within 7 ns deviates from the trapped particle location. The LIBS acquisition field of view was expanded using the 19-bundle fiber, which also reduces the fluctuation of a single particle signal. In addition, gated Raman was utilized to suppress the fluorescence and increase the Raman signal-to-noise ratio. Based on this, Raman can measure hard-to-ionize substances with LIBS, such as sulfates. The LIBS radical can overcome the restriction that Raman cannot detect ionic chemicals like fluoride and chloride in halogens. To test the capability of directly identifying distinctive feature compounds utilizing spectra, we detected anions using Raman spectroscopy and cations using LIBS. Four typical mineral aerosols are subjected to precise qualitative evaluations (marble, gypsum, baking soda, and activated carbon adsorbed potassium bicarbonate). To further validate the application potential for substances with indistinctive feature discrimination, we employed machine learning algorithms to conduct a qualitative analysis of the coal aerosol from ten different origin regions. Three data fusion methodologies (early fusion, intermediate fusion, and late fusion) for Raman and LIBS are implemented, respectively. The accuracy of the late fusion model prediction using StackingClassifier is higher than that of the LIBS data (66.7%) and Raman data (86.1%) models, with an average accuracy of 90.6%. This research has the potential to provide online single aerosol analysis as well as technical assistance for aerosol monitoring and early warning.

Self-absorption correction method for one-point calibration laser-induced breakdown spectroscopy.

As an important variant of calibration-free laser-induced breakdown spectroscopy (CF-LIBS), one-point calibration LIBS (OPC-LIBS) corrects the Boltzmann plot of the unknown sample by using one known sample and obtains higher quantitative accuracy than CF-LIBS. However, the self-absorption effect restricts its accuracy. In this work, a new self-absorption correction (SAC) method for OPC-LIBS is proposed to solve this problem. This method uses an algorithm to correct the self-absorption and does not require the calculation of the self-absorption coefficient. To verify the effectiveness of this SAC method, Ti, V, and Al elements in two titanium alloys were determined by classical OPC-LIBS and OPC-LIBS with SAC. The average relative errors (AREs) of all elements in the two samples were decreased from 8.78% and 9.28% to 8.07% and 7.56%, respectively. The results demonstrated the effectiveness of this SAC method for OPC-LIBS.

Cryptotanshinone protects skin cells from ultraviolet radiation-induced photoaging via its antioxidant effect and by reducing mitochondrial dysfunction and inhibiting apoptosis.

The integrity of skin tissue structure and function plays an important role in maintaining skin rejuvenation. Ultraviolet (UV) radiation is the main environmental factor that causes skin aging through photodamage of the skin tissue. Cryptotanshinone (CTS), an active ingredient mianly derived from the Salvia plants of Lamiaceae, has many pharmacological effects, such as anti-inflammatory, antioxidant, and anti-tumor effects. In this study, we showed that CTS could ameliorate the photodamage induced by UV radiation in epidermal keratinocytes (HaCaT) and dermal fibroblasts (HFF-1) when applied to the cells before exposure to the radiation, effectively delaying the aging of the cells. CTS exerted its antiaging effect by reducing the level of reactive oxygen species (ROS) in the cells, attenuating DNA damage, activating the nuclear factor E2-related factor 2 (Nrf2) signaling pathway, and reduced mitochondrial dysfunction as well as inhibiting apoptosis. Further, CTS could promote mitochondrial biosynthesis in skin cells by activating the AMP-activated protein kinase (AMPK)/sirtuin-1 (SIRT1)/peroxisome proliferator-activated receptor-γ co-activator-1α (PGC-1α) signaling pathway. These findings demonstrated the protective effects of CTS against UV radiation-induced skin photoaging and provided a theoretical and experimental basis for the application of CTS as an anti-photodamage and anti-aging agent for the skin.

Cucurbitacin promotes hair growth in mice by inhibiting the expression of fibroblast growth factor 18.

Background: The inhibition of fibroblast growth factor 18 (FGF18) promotes the transition of hair follicles (HFs) from the telogen phase to the anagen phase. Cucurbitacin has been shown to have a good effect in promoting hair cell growth. This study explored the potential effect of cucurbitacin on hair growth and its effect on FGF18 expression in mice. Methods: Male C57BL/6J mice were randomly divided into the following two groups: (I) the vehicle group; and (II) the cucurbitacin group. Matrix cream and cucurbitacin cream were applied to the depilated skin on the back of the vehicle group mice and the cucurbitacin group mice, respectively. On days 3, 6, 9, 12, 15, and 18, the hair growth in the depilated dorsal skin of the mice was recorded with a digital camera and a HF detector, and the HF cycle status of the mice was observed by hematoxylin and eosin (H&E) staining. In addition, the level of FGF18 messenger ribonucleic acid (mRNA) in the dorsal skin was measured on days 15 and 18 by quantitative real-time polymerase chain reaction (qRT-PCR), while the level of FGF18 protein was measured by western blot and immunofluorescence staining. Results: The dorsal skin to which the cucurbitacin cream was applied began to darken on day 6 and grew hairs on day 9, which was 3 days earlier than the dorsal skin to which the matrix cream was applied. The H&E staining revealed a transition from the telogen phase to the anagen phase 3 days earlier for the cucurbitacin cream-treated skin than the matrix cream-treated skin. In addition, the skin treated with cucurbitacin cream also showed a significant decrease in FGF18 mRNA as seen by qRT-PCR, and reduced FGF18 protein levels as detected by western blot and immunofluorescence staining compared to the skin treated with matrix cream only. Conclusions: Cucurbitacin significantly reduced the levels of FGF18 mRNA and protein in the dorsal skin of mice to accelerate the HFs to enter the anagen phase earlier, thereby promoting the regeneration of hair. Thus, cucurbitacin can be considered a new and valuable agent for the development of anti-hair loss products.

Time-Resolved Laser-Induced Breakdown Spectroscopy for Accurate Qualitative and Quantitative Analysis of Brown Rice Flour Adulteration.

To solve the adulteration problem of brown rice flour in the commodity market, a novel, accurate, and stable detection method based on time-resolved laser-induced breakdown spectroscopy (TR-LIBS) is proposed. Qualitative and quantitative analysis was used to detect five adulterants and seven different adulterant ratios in brown rice flour. Being able to excavate more information from plasma by obtaining time-resolved spectra, TR-LIBS has a stronger performance, which has been further verified by experiments. For the qualitative analysis of adulterants, the traditional machine learning models based on TR-LIBS, linear discriminant analysis (LDA), naïve Bayes (NB) and support vector machine (SVM) have significantly better classification accuracy than those based on traditional LIBS, increasing by 3-11%. The deep learning classification model based on TR-LIBS also achieved the same results, with an accuracy increase of more than 8%. For the quantitative analysis of the adulteration ratio, compared with traditional LIBS, the quantitative model based on TR-LIBS reduces the limit of detection (LOD) of five adulterants from about 8-51% to 4-19%, which effectively improves the quantitative detection performance. Moreover, t-SNE visualization proved that there were more obvious boundaries between different types of samples based on TR-LIBS. These results demonstrate the great prospect of TR-LIBS in the identification of brown rice flour adulteration.

Laser ultrasonic improvement and its application in defect detection based on the composite coating method.

Herein, we studied the increasing tendency of photoacoustic (PA) conversion efficiency of the Au/polydimethylsiloxane (PDMS) composite. The thickness of the Au layer was optimized by modeling the PA process based on the Drude-Lorentz model and finite element analysis method, and corresponding results were verified. The results showed that the optimal Au thickness of the Au/PDMS composite was 35 nm. Finally, the Au/PDMS composites were coated onto the surface of aluminum alloys, which improved the thermoelastic laser ultrasonic (LU) signals to near 100 times. Besides, the defect mapping was performed by thermoelastic LU signals with Au/PDMS coating and ablation LU signals without coating; the Pearson correlation coefficient was higher than 0.95. The application in the defect detection in metal could provide guides for nondestructive detection on metals by laser ultrasound.

Time-resolved spectral-image laser-induced breakdown spectroscopy for precise qualitative and quantitative analysis of milk powder quality by fully excavating the matrix information.

A novel and effective method named time-resolved spectral-image laser-induced breakdown spectroscopy (TRSI-LIBS) was proposed to achieve precise qualitative and quantitative analysis of milk powder quality. To verify the feasibility of TRSI-LIBS, qualitative and quantitative analysis of milk powder quality was carried out. For qualitative analysis of foreign protein adulteration, the accuracy of models based on TRSI-LIBS was higher than those based on LIBS, with an accuracy improvement of about 5% to 10%. For the quantitative analysis of foreign protein adulteration and element content, the quantitative analysis models based on TSRI-LIBS also had better effect. For instance, limit of detection (LOD),determination coefficient of prediction (R2p), root-mean-square error of prediction (RMSEP) and average relative error of prediction (AREP) of quantitative model of calcium (Ca) content based on TRSI-LIBS improved from 1.47 mg/g, 0.95, 0.35 mg/g and 23.29% to 0.81 mg/g, 0.98, 0.20 mg/g and 12.60%.

Accuracy improvement of single-sample calibration laser-induced breakdown spectroscopy with self-absorption correction.

The single sample calibration laser-induced breakdown spectroscopy (SSC-LIBS) is quite suitable for the fields where the standard sample is hard to obtain, including space exploration, geology, archaeology, and jewelry identification. But in practice, the self-absorption effect of plasma destroys the linear relationship of spectral intensity and element concentration based on the Lomakin-Scherbe formula which is the guarantee of the high accuracy of the SSC-LIBS. Thus, the self-absorption effect limits the quantitative accuracy of SSC-LIBS greatly. In this work, an improved SSC-LIBS with self-absorption correction (SSC-LIBS with SAC) is proposed for the promotion of quantitative accuracy of SSC-LIBS. The SSC-LIBS with SAC can correct the intensity ratio of spectral lines in the calculation of SSC-LIBS through relative self-absorption coefficient K without complicated preparatory information. The alloy samples and pressed ore samples were used to verify the effect of the SSC-LIBS with SAC. Compared with SSC-LIBS, for alloy samples, the average RMSEP and average ARE of SSC-LIBS with SAC decreased from 0.83 wt.% and 13.75% to 0.40 wt.% and 4.06%, respectively. For the pressed ore samples, the average RMSEP and average ARE of SSC-LIBS with SAC decreased from 4.77 wt.% and 90.48% to 2.34 wt.% and 14.60%. The experimental result indicates that SSC-LIBS with SAC has a great improvement of quantitative accuracy and better universality compared with traditional SSC-LIBS, which is a mighty promotion of the wide application of SSC-LIBS.

Indirect quantitative analysis of soluble solid content in citrus by the leaves using hyperspectral imaging combined with machine learning.

Due to the effect of bagging on fruit growth, non-destructive and in situ soluble solid content (SSC) in citrus detection remains a challenge. In this work, a new method for accurately quantifying SSC in citrus using hyperspectral imaging of citrus leaves was proposed. Sixty-five Ehime Kashi No. 28 citruses with surrounding leaves picked at two different times were picked for the experiment. Using the principal components analysis combined with Gaussian process regression model, the correlation coefficients of prediction-real value by citrus and its leaves in cross-validation were 0.972 and 0.986, respectively. In addition, the relationship between citrus leaves and SSC content was further explored, and the possible relationship between chlorophyll in leaves and SSC of citrus was analyzed. Comparing the quantitative analysis results by citrus and its leaves, the results show that the proposed method is a non-destructive and reliable method for determining the SSC by citrus leaves and has broad application prospects in indirect detection of citrus.

A method for improving the accuracy of calibration-free laser-induced breakdown spectroscopy by exploiting self-absorption.

The existence of the self-absorption effect results in a nonlinear relationship between spectral intensity and elemental concentration, which dramatically affect the quantitative accuracy of laser-induced breakdown spectroscopy (LIBS), especially calibration-free LIBS (CF-LIBS). In this work, the CF-LIBS with columnar density and standard reference line (CF-LIBS with CD-SRL) was proposed to improve the quantitative accuracy of CF-LIBS analysis by exploiting self-absorption. Our method allows using self-absorbed lines to perform the calibration-free approach directly and does not require self-absorption correction algorithms. To verify this method, the experiment was conducted both on aluminium-bronze and aluminium alloy samples. Compared with classical CF-LIBS, the average errors (AEs) of CF-LIBS with CD-SRL were decreased from 3.20%, 3.22%, 3.15% and 3.01%-0.95%, 1.00%, 1.16% and 1.78%, respectively for four aluminium-bronze alloy samples. The AEs were decreased from 0.66%, 0.70%, 0.89% and 1.30%-0.43%, 0.61%, 0.77% and 0.33%, respectively for four aluminium alloy samples. The experimental results demonstrated that CF-LIBS with CD-SRL provided higher quantitative accuracy and stronger adaptability than classical CF-LIBS, which is quite helpful for the practical application of CF-LIBS.

Suppression of FGF5 and FGF18 Expression by Cholesterol-Modified siRNAs Promotes Hair Growth in Mice.

FGF5 and FGF18 are key factors in the regulation of the hair follicle cycle. FGF5 is overexpressed during the late anagen phase and serves as a crucial regulatory factor that promotes the anagen-to-catagen transition in the hair follicle cycle. FGF18, which is overexpressed during the telogen phase, mainly regulates the hair follicle cycle by maintaining the telogen phase and inhibiting the entry of hair follicles into the anagen phase. The inhibition of FGF5 may prolong the anagen phase, whereas the inhibition of FGF18 may promote the transition of the hair follicles from the telogen phase to the anagen phase. In the present study, we used siRNA to suppress FGF5 or FGF18 expression as a way to inhibit the activity of these genes. Using qPCR, we showed that FGF5-targeting siRNA modified by cholesterol was more effective than the same siRNA bound to a cell-penetrating peptide at suppressing the expression of FGF5 both in vitro and in vivo. We then investigated the effects of the cholesterol-modified siRNA targeting either FGF5 or FGF18 on the hair follicle cycle in a depilated area of the skin on the back of mice. The cholesterol-modified siRNA, delivered by intradermal injection, effectively regulated the hair follicle cycle by inhibiting the expression of FGF5 and FGF18. More specifically, intradermal injection of a cholesterol-modified FGF5-targeted siRNA effectively prolonged the anagen phase of the hair follicles, whereas intradermal injection of the cholesterol-modified FGF18-targeted siRNA led to the mobilization of telogen follicles to enter the anagen phase earlier. The inhibitory effect of the cholesterol-modified FGF18-targeted siRNA on FGF18 expression was also evaluated for a topically applied siRNA. Topical application of a cream containing the cholesterol-modified FGF18-targeted siRNA on a depilated area of the skin of the back of mice revealed comparable inhibition of FGF18 expression with that observed for the same siRNA delivered by intradermal injection. These findings suggested that alopecia could be prevented and hair regrowth could be restored either through the intradermal injection of cholesterol-modified siRNA targeting FGF5 or FGF18 or the topical application of FGF18 siRNA.

Oat ß-glucan ameliorates epidermal barrier disruption by upregulating the expression of CaSR through dectin-1-mediated ERK and p38 signaling pathways.

The integrity of the epidermal barrier and the maintenance of barrier homeostasis depend on the dynamic balance between the proliferation and differentiation of keratinocytes. Calcium (Ca2+) plays a crucial role in maintaining a balance of these two processes as well as in the formation of an epidermal permeability barrier. In this study, we showed that topical application of oat ß-glucan (OG) could ameliorate epidermal hyperplasia and accelerate the recovery of the epidermal barrier by promoting epidermal differentiation. Mechanistic studies revealed a positive interaction between OG and the dectin-1 receptor, and this interaction could lead to an upregulated expression of the calcium-sensing receptor (CaSR) via activation of the downstream ERK and p38 pathways. This consequently increased the sensitivity of keratinocytes to extracellular Ca2+ under the condition of calcium loss following the disruption of the epidermal barrier, resulting in the maintenance of normal keratinocyte differentiation in the epidermis, and ultimately promoting the recovery of the epidermal barrier. These findings clearly demonstrated the healing effect of OG on a physically damaged epidermal barrier. Thus, OG could be considered a valuable component in the development of skin repair agents.

Meat species identification accuracy improvement using sample set portioning based on joint x-y distance and laser-induced breakdown spectroscopy.

Laser-induced breakdown spectroscopy (LIBS) was suitable for the identification of meat species due to fast and less sample preparation. However, the problem of low accuracy rate of the recognition model caused by improper selection of training set samples by random split has severely restricted the development of LIBS in meat detection. Sample set portioning based on the joint x-y distance (SPXY) method was applied for dividing the meat spectra into a training set and a test set. Then, the five kinds of meat samples (shrimp, chicken, beef, scallop, and pig liver) were classified by the support vector machine (SVM). With the random split method, Kennard-Stone method, and SPXY method, the recognition accuracies of the SVM model were 90.44%, 91.95%, and 94.35%, respectively. The multidimensional scaling method was used to visualize the results of the sample split for the interpretation of the classification. The results showed that the identification performance of the SPXY method combined with the SVM model was best, and the accuracy rates of shrimp, chicken, beef, scallop, and pig liver were 100.00%, 100.00%, 100.00%, 78.57%, and 92.00%, respectively. Moreover, to verify the broad adaptability of the SPXY method, the linear discriminant analysis model, the K-nearest neighbor model, and the ensemble learning model were applied as the meat species identification model. The results demonstrated that the accuracy rate of the classification model can be improved with the SPXY method. In light of the findings, the proposed sample portioning method can improve the accuracy rate of the recognition model using LIBS.

Keratinocyte Growth Factor 2 Ameliorates UVB-Induced Skin Damage via Activating the AhR/Nrf2 Signaling Pathway.

Objective: Exposure to ultraviolet B (UVB) can cause skin damage through oxidative stress, DNA damage, and apoptosis. Keratinocyte growth factor (KGF) has been shown to reduce the content of intracellular reactive oxygen species (ROS) following UVB exposure, a role that is crucial for the efficient photoprotection of skin. The present study evaluated the photoprotective effect of KGF-2 on UVB-induced skin damage and explored its potential molecular mechanism. Methods: To evaluate the effect of KGF-2 on UVB-induced damage ex vivo, a human epidermal full-thickness skin equivalent was pretreated without or with KGF-2 and then exposed to UVB and the levels of histopathological changes, DNA damage, inflammation, and apoptosis were then evaluated. The ability of KGF-2 to protect the cells against UVB-inflicted damage and its effect on ROS production, apoptosis, and mitochondrial dysfunction were determined in HaCaT cells. Results: Pretreatment of the epidermis with KGF-2 ameliorated the extent of photodamage. At the cellular level, KGF-2 could attenuate ROS production, apoptosis, DNA damage, and mitochondrial dysfunction caused by UVB exposure. KGF-2 could also activate the aryl hydrocarbon receptor (AhR) to trigger the Nrf2 signaling pathway. Conclusion: Taken together, our findings suggested that KGF-2 could ameliorate UVB-induced skin damage through inhibiting apoptosis, reducing oxidative stress, and preventing DNA damage and mitochondrial dysfunction via regulating AhR/Nrf2 signaling pathway.

Stable and ultrasensitive analysis of organic pollutants and heavy metals by dried droplet method with superhydrophobic-induced enrichment.

Herein, a dried droplet method (DDM) with superhydrophobic-induced enrichment is reported for stable and ultrasensitive analysis of organic pollutants and heavy metals. A superhydrophobic (SHB) substrate was prepared as an analytical detection platform for the DDM. This SHB substrate was synthesized by sequentially coating polydimethylsiloxane (PDMS) and titanium dioxide nanoparticles (TiO2 NPs) onto glass substrate surface. In the droplet drying process, the SHB substrate was demonstrated to suppress the coffee ring effect (CRE) and enriched analyte concentration. Combining with Raman spectroscopy for analysis of methylene blue (MB), and with laser-induced breakdown spectroscopy (LIBS) for analysis of chromium (Cr), the results indicated high stability and ultra-sensitivity for organic pollutants and heavy metals detection. Overall, the DDM with superhydrophobic-induced enrichment has big potential in applications requiring stable and ultrasensitive analysis.