[Expression and Clinical Significance of LINC00475 in Multiple Myeloma].

OBJECTIVE: To investigate the relative expression level and clinical significance of LINC00475 in serum of patients with multiple myeloma (MM). METHODS: The expression of LINC00475 in serum of 108 MM patients and five MM cell lines including RPMI 8226, NCI-H929, U266, OPM2 and CAG were detected by real-time fluorescence quantitative PCR. The diagnostic value of LINC00475 in MM was evaluated by receiver operating characteristic (ROC) curve analysis. The correlation of LINC00475 with patients' characteristics was analyzed. RESULTS: Compared with control groups, the expression of LINC00475 was up-regulated in serum of MM patients and MM cell lines (all P < 0.05). ROC curve analysis showed that the optimal cut-off value of LINC00475 was 262.4, the area under curve (AUC) was 0.924(95%CI : 0.884-0.964), and sensitivity and specificity was 83.3% and 91.7%, respectively, which indicated that LINC00475 had good evaluation value in MM patients. Compared with low-LINC00475 expression group, patients in high-LINC00475 expression group had higher levels of ß2microglobulin (ß2-MG) and Cystatin C (Cys-C) but lower albumin (ALB) (all P < 0.05). Compared with MM patients with International Staging System (ISS) stage I, the expression level of LINC00475 was significantly higher in patients with stage II and III (both P < 0.05). CONCLUSION: LINC00475 is helpful to distinguish MM patients from healthy adults, which is correlated with the prognostic indicators such as ß2-MG, ALB, and ISS stage.

[Pollution Characteristics and Source Analysis of Soil Heavy Metal in Coal Mine Area near the Yellow River in Shandong].

To explore the pollution characteristics and source of soil heavy metal in a coal mine area near the Yellow River in Shandong, the geo-accumulation index method and improved Nemerow pollution index method were used to evaluate the pollution characteristics of soil heavy metal. The absolute principal component-multiple linear regression model (APCS-MLR) was used to quantitatively analyze the source of soil heavy metal, and the spatial distribution of Hg and Cd were analyzed using the Kriging spatial difference method in ArcGIS. The result accuracy of the APCS-MLR model was further verified. The results showed that:The measured contents of soil heavy metal Cu, Zn, Pb, Cr, Cd, Ni, As, and Hg all exceeded the normal site, among which, Hg and Cd exceeded the background values of soil elements in Shandong. The coefficient of variation (CV) of Hg was higher than 0.500, indicating significant spatial heterogeneity. Moreover, the correlation between Hg and other heavy metals was generally low, and the possibility of the same pollution source was small. The results of the geo-accumulation index and improved Nemerow pollution index showed that the overall soil heavy metal pollution was at a moderate level, among which the Hg pollution level was the highest, and its maximum value was at a slanted-heavy pollution level; Cu, Cd, and As in soil caused local pollution, which were at a slanted-light pollution level. Soil heavy metal pollution was closely related to mining activities, rehabilitation, and engineering construction in the coal mine area. The two major pollution sources of soil heavy metal in the research area were the compound source of the parent material and industrial and mining transportation sources (known source 1) and the compound source of atmospheric sedimentation and coal production (known source 2), the contribution rates of which were 76.705% and 16.171%, respectively. The results of the APCS-MLR model were shown to be reliable by analyzing the content distribution of Hg and Cd using the Kriging space difference mode. This research can provide scientific basis for the precise control and improvement of soil heavy metal pollution, ensuring the safety of food and agricultural products and improving the quality of the ecological environment in the coal mine area in the Shandong section of the Yellow River Basin.

Comparison of different corneal residual bed thickness after small incision lenticule extraction (SMILE).

PURPOSE: To evaluate the corneal biological parameters stability between the different corneal residual bed thickness (RBT) after Small Incision Lenticule Extraction (SMILE). METHODS: In this prospective clinical trial, 127 eyes of 64 patients underwent SMILE. According to the corneal RBT, the patients were divided into the 250-270 µm, 270-290 µm and 290-310 µm groups. Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany) and Scheimpflug camera (Pentacam; Oculus Optikgeräte GmbH, Wetzlar, Germany) measurements were performed preoperatively, 1 day, 1week, 1month and 3 months after surgery. RESULTS: The keratometer values among the three groups were no significant differences in postoperative periods (each P > 0.05), except the corneal thickness values (each P < 0.05). In the 250-270 µm and 270-290 µm groups, the keratometer and corneal thickness values were decreased at postoperative 1 week and increased at 1 and 3 months. The 290-310 µm group significantly higher posterior maximum elevation (PME) than the 250-270 µm group at 1 and 3 months (P = 0.022, 0.022, respectively), and higher preoperative thinnest point (PTE) at 1 week and 1 month (P = 0.013, 0.035, respectively). The PME of the 290-310 µm group was higher than the 270-290 µm group at 3 months (P = 0.045), and higher PTE at 1 week and 3 months (P = 0.022, 0.02, respectively). In all three groups, the maximal deformation amplitude (DA) was significantly higher at 1 and 3 months compared to postoperative 1 day and 1 week, and the IOP was decreased at 1 month then recovered at 3 months (each P < 0.05).The DA of the 250-270 µm group was significantly higher than the 290-310 µm group at postoperative 1 week, 1 and 3 months (P = 0.001, 0.01, 0.02, respectively). The change of the posterior corneal elevation and biomechanical parameters values were no significant differences among the three groups in postoperative periods (each P > 0.05). CONCLUSIONS: The range of 250-310 µm RBT was safe and stable at the early postoperative of SMILE. The RBT may be positively correlated with the posterior corneal elevation.

Mask R-CNN provides efficient and accurate measurement of chondrocyte viability in the label-free assessment of articular cartilage.

Objective: Chondrocyte viability (CV) can be measured with the label-free method using second harmonic generation (SHG) and two-photon excitation autofluorescence (TPAF) imaging. To automate the image processing for the label-free CV measurement, we previously demonstrated a two-step deep-learning method: Step 1 used a U-Net to segment the lacuna area on SHG images; Step 2 used dual CNN networks to count live cells and the total number of cells in extracted cell clusters from TPAF images. This study aims to develop one-step deep learning methods to improve the efficiency of CV measurement. Method: TPAF/SHG images were acquired simultaneously on cartilage samples from rats and pigs using two-photon microscopes and were merged to form RGB color images with red, green, and blue channels assigned to emission bands of oxidized flavoproteins, reduced forms of nicotinamide adenine dinucleotide, and SHG signals, respectively. Based on the Mask R-CNN, we designed a deep learning network and its denoising version using Wiener deconvolution for CV measurement. Results: Using training and test datasets from rat and porcine cartilage, we have demonstrated that Mask R-CNN-based networks can segment and classify individual cells with a single-step processing flow. The absolute error (difference between the measured and the ground-truth CV) of the CV measurement using the Mask R-CNN with or without Wiener deconvolution denoising reaches 0.01 or 0.08, respectively; the error of the previous CV networks is 0.18, significantly larger than that of the Mask R-CNN methods. Conclusions: Mask R-CNN-based deep-learning networks improve efficiency and accuracy of the label-free CV measurement.

Management of autofluorescence in formaldehyde-fixed myocardium: choosing the right treatment.

Autofluorescence (AF) poses challenges for detecting proteins of interest in situ when employing immunofluorescence (IF) microscopy. This interference is particularly pronounced in strongly autofluorescent tissues such as myocardium, where tissue AF can be comparable to IF. Although various histochemical methods have been developed to achieve effective AF suppression in different types of tissue, their applications on myocardial  samples have not been well validated. Due to inconsistency across different autofluorescent structures in sometypes of tissue, it is unclear if these methods can effectively suppress AF across all autofluorescent structures within the myocardium. Here, we quantitatively evaluated the performance of several commonly used quenching treatments on formaldehyde-fixed myocardial samples, including 0.3 M glycine, 0.3% Sudan Black B (SBB), 0.1% and 1% sodium borohydride (NaBH4), TrueVIEW® and TrueBlack®. We further assessed their quenching performance by employing the pre-treatment and post-treatment protocols, designed to cover two common IF staining scenarios where buffers contained detergents or not. The results suggest that SBB and TrueBlack® outperform other reagents in AF suppression on formaldehyde-fixed myocardial samples in both protocols. Furthermore, we inspected the quenching performance of SBB and TrueBlack® on major autofluorescent myocardial structures and evaluated their influence on IF imaging. The results suggest that SBB outperforms TrueBlack® in quenching major autofluorescent structures, while TrueBlack® excels in preserving IF labeling signal. Surprisingly, we found the treatment of NaBH4 increased AF signal and enhanced the AF contrast of major autofluorescent structures. This finding suggests that NaBH4 has the potential to act as an AF enhancer and may facilitate the interpretation of myocardial structures without the need for counterstaining.

Measuring chondrocyte viability of articular cartilage based on label-free two-photon microscopy and deep learning image analysis.

Objective: Chondrocyte viability (CV) is an important indicator of articular cartilage health. Two-photon excitation autofluorescence (TPAF) and second harmonic generation (SHG) microscopy provide a label-free method for imaging chondrocytes. In this study, we propose an automated assessment of CV using deep learning cell segmentation and counting based on acquired TPAF/SHG images. Design: Label-free TPAF/SHG images of cartilage samples from rats and porcine were acquired using both commercial and home-built two-photon microscopes, respectively. TPAF/SHG images were merged to form RGB color images with red, green, and blue channels assigned to TPAF (two channels) and SHG signals, respectively. To make the training datasets for the deep learning networks, individual chondrocyte areas on the RGB color images were manually circled and live or dead chondrocytes were validated by using Calcein-AM and Ethidium homodimer-1 dye labeling. We first built a chondrocyte viability network (MCV-Net) using the Mask R-CNN architecture, which could provide individual segmented cellular areas with live or dead status. Wiener deconvolution preprocessing was added before the input of MCV-Net to improve the accuracy of the CV analysis, forming the Wiener deconvolution CV network (wMCV-Net). Results: Training (300 images) and test (120 images) datasets were built for rats and porcine cartilage respectively. Wiener deconvolution could improve the Peak Signal-to-Noise Ratio (PSNR) for 30-40%. We demonstrated that both MCV-Net and wMCV-Net significantly improved the accuracy of the CV measurement. Conclusion: A custom desktop TPAF/SHG microscope was used in collaboration with deep learning algorithm wMCV-Net based label-free method to assess the CV and get 95% accuracy with both rats and porcine samples.

Comparison of corneal biological parameters between transepithelial and epithelium-off corneal cross-linking in keratoconus.

AIM: To evaluate the differences in corneal biological parameters between transepithelial and epithelium-off corneal cross-linking in keratoconus. METHODS: In our prospective clinical trial, 40 patients (60 eyes) with progressive keratoconus were randomized to undergo corneal cross-linking with transepithelial (TE group, n=30) or epithelium-off (EO group, n=30) keratoconus. Examinations comprised topography, corneal biomechanical analysis and specular microscopy at 6mo postoperatively. RESULTS: The keratometer values were not significantly different between the TE and EO corneal cross-linked groups in different periods (each P>0.05). The corneal thickness of the EO group was greater than that of the TE group at 1wk after the operation (each P<0.05). Regarding corneal biomechanical responses, the EO group showed a longer second applanation length than TE group (P=0.003). Regarding the corneal endothelial function, standard deviation of the endothelial cell size, and coefficient of variation in the cell area, the values of EO group were larger than those of TE group at 1wk (P=0.011, 0.026), and the percentage of hexagonal cells in EO group was lower than that in TE group at 1 and 6mo (P=0.018, 0.019). CONCLUSION: Epithelium-off corneal cross-linking may strengthen corneal biomechanics better than TE procedure can. However, the TE procedure with a lower ultraviolet-A irradiation intensity would be safer for corneal endothelial function.

Deep learning provides high accuracy in automated chondrocyte viability assessment in articular cartilage using nonlinear optical microscopy.

Chondrocyte viability is a crucial factor in evaluating cartilage health. Most cell viability assays rely on dyes and are not applicable for in vivo or longitudinal studies. We previously demonstrated that two-photon excited autofluorescence and second harmonic generation microscopy provided high-resolution images of cells and collagen structure; those images allowed us to distinguish live from dead chondrocytes by visual assessment or by the normalized autofluorescence ratio. However, both methods require human involvement and have low throughputs. Methods for automated cell-based image processing can improve throughput. Conventional image processing algorithms do not perform well on autofluorescence images acquired by nonlinear microscopes due to low image contrast. In this study, we compared conventional, machine learning, and deep learning methods in chondrocyte segmentation and classification. We demonstrated that deep learning significantly improved the outcome of the chondrocyte segmentation and classification. With appropriate training, the deep learning method can achieve 90% accuracy in chondrocyte viability measurement. The significance of this work is that automated imaging analysis is possible and should not become a major hurdle for the use of nonlinear optical imaging methods in biological or clinical studies.

Effect of corneal stromal pocket irrigation in small-incision lenticule extraction.

OBJECTIVES: To investigate the effect of corneal stromal pocket irrigation after small-incision lenticule extraction (SMILE) on visual acuity, intraocular pressure (IOP), corneal parameters and complications after surgery. METHODS: A total of 242 eyes of 121 patients undergoing SMILE were enrolled in this prospective controlled study, and it was designed for one eye to randomly undergo SMILE with balanced salt solution irrigation of the corneal stromal pocket, while the other eye was not. The uncorrected distance visual acuity (UDVA) and slit lamp examination were recorded at 1 hour, 1 day, 1 week, and 1 month. Postoperative corneal density, corneal biomechanical, corneal endothelial cell number, and anterior OCT images were compared at 1 day, 1 week, and 1 month. RESULTS: Compared with the nonirrigation group, the irrigation group showed significantly higher UDVA at 1 day postoperatively (P < 0.05), but there was no significant difference during the rest of the postoperative period (1 hour, 1 week, and 1 month). In addition, no significant differences were found in IOP, corneal density, corneal biomechanics, corneal endothelial cells, and corneal morphology. No visual decline or severe postoperative complications were found in the patients in this study. CONCLUSIONS: Interlamellar irrigation did not affect IOP, corneal parameters, morphology, complications, or UDVA at 1 hour, 1 week, and 1 month after the operation, but it may promote UDVA 1 day after the operation.

Coalbed methane diffusion and water blocking effects investigated by mesoscale all-atom molecular dynamic simulations.

In coalbed methane extraction processes, the water blocking effect (WBE) is a formation damage that limits the extraction efficiency. To investigate WBE mechanisms at the molecular level, realistic coal models must be developed to simulate the interplay between methane and liquid phase water in a coal matrix's mesopores and macropores. This study built a massive and highly scalable coal tube model with accurate all-atom force fields. Based on this model, we investigated the adsorption and diffusion of methane and liquid water in the mesopores of coal. We found that methane forms multiple layers of adsorption on the coal surface, and the diffusivity of methane strongly depends on pore sizes and the presence of water. When both methane and liquid water were loaded in the coal tube, the liquid phase formed a nearly impenetrable barrier that prevented methane diffusion. This work provides insights into the mechanism of the WBE and can facilitate further studies on WBE alleviating strategies.

High visibility first-order subwavelength interference based on light pulse storage via electromagnetically induced transparency.

We achieved high visibility first-order subwavelength interference based on light pulse storage and retrieval technique via electromagnetically induced transparency (EIT) effect in a Pr3+:Y2SiO5 crystal. The interference field distribution of a double-slit was first stored in a Pr3+:Y2SiO5 crystal based on EIT effect, and then it was read out by a spatially modulated readout beam. The retrieved output field is proportional to the product of the input interference field of the double-slit and the spatially modulated readout field. High visibility first-order subwavelength interference with an effective wavelength of λ/n, where λ is the wavelength of the input light field and n is any positive integer, can be obtained by designing the spatial modulation structure of the readout field. Experimentally, first-order subwavelength interference with an effective wavelength of λ/3 and a visibility of 67% were demonstrated. Such first-order subwavelength interference has important applications on high resolution optical lithography.