Structure-function analysis of an ancient TsaD-TsaC-SUA5-TcdA modular enzyme reveals a prototype of tRNA t6A and ct6A synthetases.

N 6-threonylcarbamoyladenosine (t6A) is a post-transcriptional modification found uniquely at position 37 of tRNAs that decipher ANN-codons in the three domains of life. tRNA t6A plays a pivotal role in promoting translational fidelity and maintaining protein homeostasis. The biosynthesis of tRNA t6A requires members from two evolutionarily conserved protein families TsaC/Sua5 and TsaD/Kae1/Qri7, and a varying number of auxiliary proteins. Furthermore, tRNA t6A is modified into a cyclic hydantoin form of t6A (ct6A) by TcdA in bacteria. In this work, we have identified a TsaD-TsaC-SUA5-TcdA modular protein (TsaN) from Pandoraviruses and determined a 3.2 Å resolution cryo-EM structure of P. salinus TsaN. The four domains of TsaN share strong structural similarities with TsaD/Kae1/Qri7 proteins, TsaC/Sua5 proteins, and Escherichia coli TcdA. TsaN catalyzes the formation of threonylcarbamoyladenylate (TC-AMP) using L-threonine, HCO3- and ATP, but does not participate further in tRNA t6A biosynthesis. We report for the first time that TsaN catalyzes a tRNA-independent threonylcarbamoyl modification of adenosine phosphates, leading to t6ADP and t6ATP. Moreover, TsaN is also active in catalyzing tRNA-independent conversion of t6A nucleoside to ct6A. Our results imply that TsaN from Pandoraviruses might be a prototype of the tRNA t6A- and ct6A-modifying enzymes in some cellular organisms.

Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

BACKGROUND: Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. PURPOSE: Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. STUDY TYPE: Retrospective. POPULATION: Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. FIELD STRENGTH/SEQUENCE: 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). ASSESSMENT: The Bayesian method's performance in fitting cell diameter ( d $$ d $$ ), intracellular volume fraction ( f in $$ {f}_{in} $$ ), and extracellular diffusion coefficient ( D ex $$ {D}_{ex} $$ ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. STATISTICAL TESTS: T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. RESULTS: Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for d $$ d $$ , f in $$ {f}_{in} $$ , and D ex $$ {D}_{ex} $$ compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for f in $$ {f}_{in} $$ compared to r = 0.698 using NLLS, P = 0.5764). DATA CONCLUSION: The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Abnormal Degraded Tapetum 1 (ADT1) is required for tapetal cell death and pollen development in rice.

The timely degradation of tapetum, the innermost somatic anther cell layer in flowering plants, is critical for pollen development. Although several genes involved in tapetum development have been characterized, the molecular mechanisms underlying tapetum degeneration remain elusive. Here, we showed that mutation in Abnormal Degraded Tapetum 1 (ADT1) resulted in overaccumulation of Reactive Oxygen Species (ROS) and abnormal anther development, causing earlier tapetum Programmed Cell Death (PCD) and pollen abortion. ADT1 encodes a nuclear membrane localized protein, which is strongly expressed in the developing microspores and tapetal cells during early anther development. Moreover, ADT1 could interact with metallothionein MT2b, which was related to ROS scavenging and cell death regulation. These findings indicate that ADT1 is required for proper timing of tapetum PCD by regulating ROS homeostasis, expanding our understanding of the regulatory network of male reproductive development in rice.

Diquat causes mouse testis injury through inducing heme oxygenase-1-mediated ferroptosis in spermatogonia.

Diquat dibromide (DQ) is a globally used herbicide in agriculture, and its overuse poses an important public health issue, including male reproductive toxicity in mammals. However, the effects and molecular mechanisms of DQ on testes are limited. In vivo experiments, mice were intraperitoneally injected with 8 or 10 mg/kg/ day of DQ for 28 days. It has been found that heme oxygenase-1 (HO-1) mediates DQ-induced ferroptosis in mouse spermatogonia, thereby damaging testicular development and spermatogenesis. Histopathologically, we found that DQ exposure caused seminiferous tubule disorders, reduced germ cells, and increased sperm malformation, in mice. Reactive oxygen species (ROS) staining of frozen section and transmission electron microscopy (TEM) displayed DQ promoted ROS generation and mitochondrial morphology alterations in mouse testes, suggesting that DQ treatment induced testicular oxidative stress. Subsequent RNA-sequencing further showed that DQ treatment might trigger ferroptosis pathway, attributed to disturbed glutathione metabolism and iron homeostasis in spermatogonia cells in vitro. Consistently, results of western blotting, measurements of MDA and ferrous iron, and ROS staining confirmed that DQ increased oxidative stress and lipid peroxidation, and accelerated ferrous iron accumulation both in vitro and in vivo. Moreover, inhibition of ferroptosis by deferoxamine (DFO) markedly ameliorated DQ-induced cell death and dysfunction. By RNA-sequencing, we found that the expression of HO-1 was significantly upregulated in DQ-treated spermatogonia, while ZnPP (a specific inhibitor of HO-1) blocked spermatogonia ferroptosis by balancing intracellular iron homeostasis. In mice, administration of the ferroptosis inhibitor ferrostatin-1 effectively restored the increase of HO-1 levels in the spermatogonia, prevented spermatogonia death, and alleviated the spermatogenesis disorders induced by DQ. Overall, these findings suggest that HO-1 mediates DQ-induced spermatogonia ferroptosis in mouse testes, and targeting HO-1 may be an effective protective strategy against male reproductive disorders induced by pesticides in agriculture.

Effects of multi-walled carbon nanotubes and halloysite nanotubes on plasma lipid profiles and autophagic lipolysis pathways in mouse aortas and hearts.

Multi-walled carbon nanotubes (MWCNTs) and halloysite nanotubes (HNTs) are widely used tubular-structured nanomaterials (NMs), but their cardiovascular effects are not clear. This study compared the effects of MWCNTs and HNTs on lipid profiles in mouse plasma and gene expression profiles in aortas and hearts. Mice were intravenously injected with 50 µg NMs, once a day, for 5 days. Then, the plasma was collected for lipidomics analysis, and aortas and hearts were collected for RNA-sequencing analysis. While MWCNTs or HNTs did not induce obvious pathological changes in aortas or hearts, the lipid profiles in mouse plasma were altered. Further analysis revealed that MWCNTs more effectively upregulated sphingolipids and sterol lipids, whereas HNTs more effectively upregulated glycerophospholipids and fatty acyls. Consistently, RNA-sequencing data indicated that MWCNTs and HNTs altered signaling pathways related with lipid synthesis and metabolism, as well as those related with endoplasmic reticulum, lysosomes and autophagy, more significantly in aortas than in hearts. We further verified the changes of proteins involved in autophagic lipolysis, that MWCNTs were more effectively to suppress the autophagic biomarker LC3, whereas HNTs were more effectively to affect lipid metabolism proteins. These results may provide novel understanding about the influences of MWCNTs and HNTs on lipid profiles and lipid signaling pathways in cardiovascular systems. Importantly, previous studies considered HNTs as biocompatible materials, but the results from this study suggested that both MWCNTs and HNTs were capable to affect lipid profiles and autophagic lipolysis pathways in cardiovascular systems, although their exact influences were different.

linc00511 Knockdown Inhibits Lung Cancer Progression by Regulating miR-16-5p/MMP11.

Lung cancer (LC) is a malignant tumor that extremely impairs people. According to numerous studies, long non-coding RNA (lncRNA) was inextricably involved in the advancement of LC. The work aspired to identify linc00511 expression in LC and to dig for the underlying mechanisms linc00511 regulated LC progression. Experimental outcomes revealed that linc00511 was obviously upregulated in LC, and linc00511 knockdown significantly impaired the malignant phenotype of LC cells in vitro. For an in-depth study on the contribution of linc00511 to LC advancement, it was disclosed that miR-16-5p had binding sites to the sequence of linc00511, which also inversely affected linc00511 expression in LC. Further experimental data demonstrated that miR-16-5p directly and negatively targeted matrix metallopeptidase 11 (MMP11). Also, rescue experiments displayed that miR-16-5p inhibition or MMP11 overexpressing offset the suppressive impacts of linc00511 silencing on LC progression. To sum up, our findings indicated that linc00511 performed a crucial role in facilitating LC progression, and mechanistic studies demonstrated that linc00511 aggravated LC progression via targeting the miR-16-5p/MMP11 axis.

The Diagnosis of Chronic Myeloid Leukemia with Deep Adversarial Learning.

Chronic myeloid leukemia (CML) is a clonal proliferative disorder of granulocytic lineage, with morphologic evaluation as the first step for a definite diagnosis. This study developed a conditional generative adversarial network (cGAN)-based model, CMLcGAN, to segment megakaryocytes from myeloid cells in bone marrow biopsies. After segmentation, the statistical characteristics of two types of cells were extracted and compared between patients and controls. At the segmentation phase, the CMLcGAN was evaluated on 517 images (512 × 512) which achieved a mean pixel accuracy of 95.1%, a mean intersection over union of 71.2%, and a mean Dice coefficient of 81.8%. In addition, the CMLcGAN was compared with seven other available deep learning-based segmentation models and achieved a better segmentation performance. At the clinical validation phase, a series of seven-dimensional statistical features from various cells were extracted. Using the t-test, five-dimensional features were selected as the clinical prediction feature set. Finally, the model iterated 100 times using threefold cross-validation on whole slide images (58 CML cases and 31 healthy cases), and the final best AUC was 84.93%. In conclusion, a CMLcGAN model was established for multiclass segmentation of bone marrow cells that performed better than other deep learning-based segmentation models.

Low crosstalk trapezoid-index thirteen-core single-mode fiber for multi-channel and high-density applications.

Multi-core fiber based on space division multiplexing technology provides a practical solution to achieve multi-channel and high-capacity signal transmission. However, long-distance and error-free transmission remains challenging due to the presence of inter-core crosstalk within the multi-core fiber. Here, we propose and prepare a novel trapezoid-index thirteen-core single-mode fiber to solve the problems that MCF has large inter-core crosstalk and the transmission capacity of single-mode fiber approaches the upper limit. The optical properties of thirteen-core single-mode fiber are measured and characterized by experimental setups. The inter-core crosstalk of the thirteen-core single-mode fiber is less than -62.50 dB/km at 1550 nm. At the same time, each core can transmit signals at a data rate of 10 Gb/s and achieve error-free signal transmission. The prepared optical fiber with a trapezoid-index core provides a new and feasible solution for reducing inter-core crosstalk, which can be loaded into current communication systems and applied in large data centers.

Transmissive fluorescent temperature sensor based on Er3+/Yb3+/Mo6+ tri-doped tellurite fiber for real-time thermal monitoring of motors using the FIR technique.

In this paper, we fabricate a transmissive fluorescent temperature sensor (TFTS) that based on Er3+/Yb3+/Mo6+ tri-doped tellurite fiber, which has the advantages of compactness and simplicity, corrosion resistance, high stability and anti-electromagnetic interference. The doping of Mo6+ ions will enhance the up-conversion (UC) fluorescence emission efficiency of Er3+ ions, thus improving the signal-to-noise ratio of TFTS. Using the fluorescence intensity ratio (FIR) technique, the real-time thermal monitoring performance of TFTS is evaluated experimentally. Apart from good stability, its maximum relative sensitivity is 0.01068 K-1 at 274 K in the measured temperature range. In addition, it is successfully used to monitor the temperature variation of the stator core and stator winding of the motor in actual operation. The results show that the maximum error between the FIR-demodulated temperature and the reference temperature is less than 1.2 K, which fully confirms the effectiveness of the TFTS for temperature monitoring. Finally, the FIR-based TFTS in this work is expected to provide a new solution for accurate and real-time thermal monitoring of motors and the like.

Two fiber-bundle-type FI/FO devices of low insertion loss and cross talk applied for connecting 13-core 5-mode fiber.

Two fiber-bundle-typed fan-in/fan-out (FI/FO) devices, "wavy hexagon-shaped silhouette" type (W-FI/FO) and "tortoise-shaped silhouette" type (T-FI/FO), have been proposed and manufactured based on tapering glass tubes for docking with a self-made 13-core 5-mode fiber. The W-FI/FO device consists of 19 5-mode fibers and has an extended layout based on the 13-core 5-mode fiber structure. It could dock multiple fibers with 19 or 13 cores of the same size standards. When connecting it with 13-core 5-mode, the average losses (ILs) of its five modes are 1.07 dB, 2.95 dB, 3.42 dB, 3.65 dB, and 4.38 dB. The cross talks of the five linearly polarized (LP) modes are -69.1 dB, -64.7 dB, -44.2 dB, -43.9 dB, and -39.1 dB. The T-FI/FO device has a similar core arrangement to the 13-core 5-mode fiber and its average ILs of the five LP modes are 0.23 dB, 1.31 dB, 2.09 dB, 2.66 dB, and 3.03 dB. The cross talks of its five LP modes between adjacent cores are -72.8 dB, -67.8 dB, -43.6 dB, -40.0 dB, and -35.3 dB. The IL and cross talk of the LP01 mode are of satisfactory values, which are 0.23 dB and -72.8 dB, respectively. These two proposed FI/FO devices are expected to be used for high-speed optical interconnection and fiber communication.

Diffusion-time dependent diffusion MRI: effect of diffusion-time on microstructural mapping and prediction of prognostic features in breast cancer.

OBJECTIVES: This study aimed to evaluate the effect of achievable td on the accuracy of microstructural mapping based on simulation and patient experiments, and investigate the feasibility of td-dMRI in distinguishing prognostic factors in breast cancer patients. METHODS: Simulation was performed using different td settings. Patients with breast cancer were enrolled prospectively between November 2020 and January 2021, who underwent oscillating and pulsed gradient encoded dMRI on a 3-T scanner using short-/long-td protocol with oscillating frequency up to 50/33 Hz. Data were fitted with a two-compartment model to estimate cell diameter (d), intracellular fraction (fin), and diffusivities. Estimated microstructural markers were used to differentiate immunohistochemical receptor status and the presence of lymph node (LN), which were correlated with histopathological measurements. RESULTS: Simulation results showed that d fitted from the short-td protocol significantly reduced estimation error than those from long-td (2.07 ± 1.51% versus 3.05 ± 1.92%, p < 0.0001) while the estimation error of fin was robust to different protocols. Among a total of 37 breast cancer patients, the estimated d was significantly higher in HER2-positive and LN-positive (p < 0.05) groups compared to their negative counterparts only using the short-td protocol. Histopathological validation in a subset of 6 patients with whole slide images showed the estimated d was highly correlated with measurements from H&E staining (r = 0.84, p = 0.03) only using the short-td protocol. CONCLUSIONS: The results indicated the necessity of short-td for accurate microstructural mapping in breast cancer. The current td-dMRI with a total acquisition time of 4.5 min showed its potential in the diagnosis of breast cancer. KEY POINTS: • Short td is important for accurate microstructural mapping in breast cancer using the td-dMRI technique, based on simulation and histological validation. • The 4.5-min td-dMRI protocol showed potential clinical value for breast cancer, given the difference in cell diameter between HER2/LN positive and negative groups.

Helicobacter pylori induces urease subunit B-specific CD8+ T cell responses in infected individuals via cytosolic pathway of cross-presentation.

BACKGROUND: Urease subunit B (UreB), a conserved and key virulence factor of Helicobacter pylori (H. pylori), can induce the host CD4+ T cell immune responses to provide protection, but less is known regarding CD8+ T cell responses. The characteristics of H. pylori-specific CD8+ T cell responses and the mechanism underlying antigen processing and presentation pathways remain unclear. This study was focus on protective antigen recombinant UreB (rUreb) to detect specific CD8+ T cell responses in vitro and elucidate the mechanism of UreB antigen processing and presentation. METHODS: The peripheral blood mononuclear cells (PBMCs) collected from H. pylori-infected individuals were stimulated with rUreB in vitro to detect specific CD8+ T cell responses after co-culture with rUreB-pulsed autologous hMDCs. Through blocking assay, we investigated the potential pathway of UreB antigen processing and presentation via the cytosolic pathway or vacuolar pathway. The cytokines production of UreB specific CD8+ T cell were evaluated as well. RESULTS: We demonstrated UreB can induce specific CD8+ T cell immune responses in H. pylori infected individuals. Importantly, we characterized that UreB were mainly processed by proteasome instead of lysosomal proteases and presented through cytosolic pathway of cross-presentation, which requires endoplasmic reticulum-Golgi transport and newly synthesized MHC-I molecules, to induce functional-specific CD8+ T cell (IFN-γ + TNF-α + Grz A+ Grz B+) responses. CONCLUSIONS: These results suggest that H. pylori UreB induces specific CD8+ T cell responses through cytosolic pathway of cross-presentation in infected individuals.

ß-Arrestin 2 Regulates Inflammatory Responses against Mycobacterium tuberculosis Infection through ERK1/2 Signaling.

Mycobacterium tuberculosis, the pathogen that causes tuberculosis, exhibits complex host-pathogen interactions. Pattern recognition receptors and their downstream signaling pathways play crucial roles in determining the outcome of infection. In particular, the scaffold protein ß-arrestin 2 mediates downstream signaling of G protein-coupled receptors. However, the role of ß-arrestin 2 in conferring immunity against M. tuberculosis has not yet been explored. We found that ß-arrestin 2 was upregulated in the lesioned regions of lung tissues in patients with tuberculosis. M. tuberculosis infection upregulated ß-arrestin 2 expression in human macrophages, and silencing of ß-arrestin 2 significantly enhanced bactericidal activity by enhancing the expression of proinflammatory cytokines such as TNF-α. ß-Arrestin 2 was shown to inhibit the activation of the TLR2/ERK1/2 pathway and its transcriptional regulation activity upon M. tuberculosis infection. Furthermore, ß-arrestin 2 transcriptionally regulates TNF-α by binding to CREB1. These observations revealed that the upregulation of ß-arrestin 2 is critical for M. tuberculosis to escape immune surveillance through an unknown mechanism. Our research offers a novel interference modality to enhance the immune response against tuberculosis by targeting ß-arrestin 2 to modulate the TLR2-ß-arrestin 2-ERK1/2-CREB1-TNF-α regulatory axis.

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus-associated oropharyngeal squamous cell carcinoma.

BACKGROUND: Understanding biological differences between different racial groups of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. METHODS: This study evaluated whether there were morphologic differences between HPV-associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis-derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin-eosin images and previously has been prognostic in HPV-associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease-free survival in their previous study, TTR , is valid for Black and White patients, separately. We also evaluated population-specific cutoffs, TB for Blacks and TW for Whites, for risk stratification. RESULTS: MuNI was statistically significantly different between Black (mean, 3.88e-4; median, 3.67e-04) and White patients (mean, 3.36e-04; median, 2.99e-04), with p = .0078. Using TTR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 (p = .002; 95% confidence interval [CI], 1.21-2.43) and in White patients with HR of 1.72 (p = .005; 95% CI, 1.18-2.51). Population-specific cutoff, TW , yielded improved HR of 1.77 (p = .003; 95% CI, 1.21-2.58) for White patients, whereas TB did not improve risk-stratification in Black patients with HR of 0.6 (p = .3; HR, 0.6; 95% CI, 0.2-1.80). CONCLUSIONS: Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population-specific prognostic biomarkers for personalized risk stratification strategies for HPV-associated OPSCC patients.

XGBoost-based intelligence yield prediction and reaction factors analysis of amination reaction.

Buchwald-Hartwig amination reaction catalyzed by palladium plays an important role in drug synthesis. In the last few years, machine learning-assisted strategies emerged and quickly gained attention. In this article, an importance and relevance-based integrated feature screening method is proposed to effectively filter high-dimensional feature descriptor data. Then, a regularized machine learning boosting tree model, eXtreme Gradient Boosting, is introduced to intelligently predict reaction performance in multidimensional chemistry space. Furthermore, convergence, interpretability, generalization, and the internal association between reaction conditions and yields are excavated, which provides intelligent assistance for the optimal design of coupling reaction system and evaluating the reaction conditions. Compared with recently published results, the proposed method requires fewer feature descriptors, takes less time, and achieves more accurate prediction accuracy.

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer.

Background Recently developed time-dependent diffusion MRI has potential in characterizing cellular tissue microstructures; however, its value in imaging prostate cancer (PCa) remains unknown. Purpose To investigate the feasibility of time-dependent diffusion MRI-based microstructural mapping for noninvasively characterizing cellular properties of PCa and for discriminating between clinically significant PCa and clinically insignificant disease. Materials and Methods Men with a clinical suspicion of PCa were enrolled prospectively between October 2019 and August 2020. Time-dependent diffusion MRI data were acquired with pulsed and oscillating gradient diffusion MRI sequences at an equivalent diffusion time of 7.5-30 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction, cellularity, and diffusivities, were estimated with a two-compartment model. These were compared for different International Society of Urological Pathology grade groups (GGs), and their performance in discriminating clinically significant PCa (GG >1) from clinically insignificant disease (benign and GG 1) was determined with a linear discriminant analysis. The fitted microstructural parameters were validated by means of correlation with histopathologic measurements. Results In the 48 enrolled men, the time-dependent diffusion MRI measurements showed that higher GG was correlated with higher intracellular volume fraction and higher cellularity (intracellular volume fraction = 0.22, 0.36, 0.34, 0.37, and 0.40 in GGs 1-5, respectively; P < .001 at one-way analysis of variance), while lower cell diameter was found at higher GGs (diameter = 23.4, 18.3, 19.2, 17.9, and 18.5 µm in GGs 1-5, respectively; P = .002). Among all measurements derived from time-dependent diffusion MRI, cellularity achieved the highest diagnostic performance, with an accuracy of 92% (44 of 48 participants) and area under the receiver operating characteristic curve of 0.96 (95% CI: 0.87, 0.99) in discriminating clinically significant PCa from clinically insignificant disease. Microstructural mapping was supported by positive correlations between time-dependent diffusion MRI-based and pathologic examination-based intracellular volume fraction (r = 0.83; P < .001). Conclusion Time-dependent diffusion MRI-based microstructural mapping correlates with pathologic findings and demonstrates promise for characterizing prostate cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Chatterjee and Oto in this issue.

Distributed strain and temperature fast measurement in Brillouin optical time-domain reflectometry based on double-sideband modulation.

A novel distributed strain and temperature fast measurement method in Brillouin optical time-domain reflectometry (BOTDR) system based on double-sideband (DSB) modulation is proposed. The single-wavelength probe light is modulated into dual-wavelength probe light with a fixed phase difference by using carrier suppressed DSB modulation. The interaction between the Brillouin scattering signals corresponding to dual-wavelength probe light forms a Brillouin beat spectrum (BBS). The distributed temperature and strain are obtained by only measuring the peak power trace of the BBS and one of the slope power trace of the two Brillouin gain spectrum (BGS) corresponding to dual-wavelength probe light. The proposed method does not require scanning the Brillouin spectrum and does not require using optical fibers with multiple Brillouin scattering peaks as sensing fibers, and thus features fast measurement speed and wide variety of sensing fiber types. In a proof-of-concept experiment, the temperature uncertainty of 1.3 °C and the strain uncertainty of 36.3 µÎµ are respectively achieved over a 4.5-km G.657 fiber with 3 m spatial resolution and 30 s measurement time. The experimental measurement uncertainties of temperature and strain of the proposed method are almost equivalent to that of the method by using BGS scanning and special fibers.

Noise reduction in a Brillouin optical time-domain sensor by a frequency-domain feature filter.

A novel frequency-domain image processing method is proposed, to the best of our knowledge, to filter the noise from data collected by distributed optical fiber sensors based on Brillouin optical time-domain sensing (BOTDS). In the proposed method, we first divide a data image into subimages, and then we filter the noisy subimages by retaining the useful frequency information corresponding to the Lorentz-shape frequency spectrum and Brillouin frequency shift (BFS) transitions. The denoising performance improvements are verified by simulation and experiment. The performances in terms of temperature/strain measurement uncertainty, spatial resolution, and processing time achieved by the proposed filter are then compared with those by using a Gaussian filter and a nonlocal means (NLM) filter. In a proof-of-concept experiment with a 5.2 km length G657 sensing fiber, we achieve a temperature measurement uncertainty improvement of 27% compared with the results obtained by using the Gaussian filtering method. Furthermore, the processing speed of the proposed method is 22 times faster than that of the NLM filter under the same temperature measurement uncertainty.

Does Garden type I incomplete femoral neck fracture really exist in older adults? To evaluate the stability and consistency of Garden classification.

BACKGROUND: Accurate classification of femoral neck fracture (FNF) is crucial for treatment plan and therapeutic outcomes. Garden classification is commonly used in the clinic, but its stability and consistency remain controversial. The aim of this study was to evaluate the stability and consistency of Garden classification based on X and CT images, and to analyze whether it is valid for Garden I in the elderly. METHODS: X-ray and CT images from 886 elderly patients with FNF were collected, four orthopaedic surgeons and four radiologists evaluated these images independently, and determined the fracture type based on Garden classification. Three months later, The exercise was repeated and the results were compared based on 4 types Garden classification (I, II, III and IV) and 3 types Garden classification (I + II, III and IV). Kappa was used to measure inter- and intraobserver agreement. The patients with Garden I incomplete FNF confirmed by 8 observers together based on images combined with medical history were compared with the intraoperative results. RESULTS: Four types Garden classification, there was little consistency inter- and intraobservers (Kappa from 0.18 to 0.43) based on X-ray images, while professors consistency (0.56 to 0.76) was higher than residents (0.28 to 0.35) based on CT. 3 types Garden classification showed almost perfect agreement inter- and intraobservers, which ranged from 0.76 to 0.90. Totally 52 patients were diagnosed as Garden I, 38 of whom underwent arthroplasty. All surgical cases showed complete fracture during operation. CONCLUSIONS: There was low consistency and repeatability in 4 types Garden classification (I, II, III and IV), while 3 types Garden classification (I + II, III and IV) had high consistency among observers. In the elderly, all undisplaced femoral neck fracture may be Garden II, no Garden I.

A Cotraining-Based Semisupervised Approach for Remaining-Useful-Life Prediction of Bearings.

The failure of bearings can have a significant negative impact on the safe operation of equipment. Recently, deep learning has become one of the focuses of RUL prediction due to its potent scalability and nonlinear fitting ability. The supervised learning process in deep learning requires a significant quantity of labeled data, but data labeling can be expensive and time-consuming. Cotraining is a semisupervised learning method that reduces the quantity of required labeled data through exploiting available unlabeled data in supervised learning to boost accuracy. This paper innovatively proposes a cotraining-based approach for RUL prediction. A CNN and an LSTM were cotrained on large amounts of unlabeled data to obtain a health indicator (HI), then the monitoring data were entered into the HI and the RUL prediction was realized. The effectiveness of the proposed approach was compared and analyzed against individual CNN and LSTM and the stacking networks SAE+LSTM and CNN+LSTM in the existing literature using RMSE and MAPE values on a PHM 2012 dataset. The results demonstrate that the RMSE and MAPE value of the proposed approach are superior to individual CNN and LSTM, and the RMSE value of the proposed approach is 54.72, which is significantly lower than SAE+LSTM (137.12), and close to CNN+LSTM (49.36). The proposed approach has also been tested successfully on a real-world task and thus has strong application value.