In-service crosstalk monitoring in multicore fibers based on precoded DMT system.

In-service crosstalk monitoring based on the precoding technique in a discrete multitone (DMT) system is proposed and validated experimentally. The method relies on the ability of time-frequency domain equalization of precoded DMT. Experiments on a 20 GBaud 16 quadrature amplitude modulation DMT system over seven-core weakly coupled multicore fibers (MCFs) are conducted. The inter-core instantaneous average crosstalk (IAXT) is gathered and evaluated in a period as short as 10 µm without disturbing the signal transmission. Such IAXT has a high correlation with the bit error ratio (BER), and a transmission performance evaluation strategy of the MCF transmitting system is developed according to the relationship between IAXT and BER.

Sparse representation of Brillouin spectrum using dictionary learning.

Distributed optical fiber Brillouin sensors can monitor the temperature and strain along a fiber by estimating the Brillouin frequency shift (BFS) according to the measured Brillouin spectrum. The system performance is highly dependent on the algorithm of BFS extraction. The well-established Lorentz curve fitting (LCF) method is generally employed because the Brillouin spectrum theoretically satisfies a Lorentz shape. Recently, machine-learning methods have been proposed for more effective BFS extraction, but they have some drawbacks and limitations. The machine-learning algorithms require a large amount of data and high computing power to find suitable extraction methods. However, with prior knowledge, Brillouin spectrum can be treated as a regular signal that requires only three degrees of freedom to define. The unique sparsity characteristics of Brillouin spectrum have not been well studied or exploited. In this paper, we propose a sparse representation method for Brillouin spectrum that extracts three sparse features of the Brillouin spectrum through the dictionary-learning algorithm (K-means singular value decomposition). The correlation between the sparse coefficient and the BFS is experimentally calibrated and verified. The accuracy of the proposed algorithm is comparable to that of LCF, and its processing is six times faster. This sparse representation method for Brillouin spectra is promising as an alternative universal BFS extraction method for distributed Brillouin sensors.

Minimally Invasive Aesthetic Suturing Technique for Anterior Aesthetic Crown Lengthening Surgery: A Case Series with 24- month Follow-Up.

BACKGROUND: A minimally invasive aesthetic suturing technique was employed in aesthetic crown lengthening surgery (ACLS). The objective of this report was to evaluate the clinical and patient- reported outcomes of this technique for ACLS. METHODS: Fifteen patients who underwent ACLS were treated utilizing the described suturing technique. Clinical parameters, including plaque index (PI), gingival index (GI), bleeding index (BI), papilla index score (PIS), early wound healing index (EHI), visual analogue scale (VAS), pink esthetic score and white esthetic score (PES/WES), were recorded at baseline, immediately post-surgery and during follow-up visits spanning 5 days to 24 months. The two-sample t-test was performed to evaluate statistical significance (α = 0.05). RESULT: 100% of the patients reported a high level of satisfaction, with a stable high postoperative VAS scores. From baseline to 5-day postoperation, there was no statistically significant increase in PI, although there was a slight deterioration observed in GI (0.13Å}0.23, P＜0.05) and BI (0.49Å}0.55, P＜ 0.05). Early wound healing (EHI 1) was achieved by all patients at 5 days post-surgery. Additionally, 3 patients exhibited changes in PIS within the initial 3 months following surgery, after which, all patients attained an optimal degree of papilla filling (degree III). CONCLUSION: The application of the minimally invasive aesthetic suturing technique in ACLS demonstrates favorable outcomes in terms of patient satisfaction and long-term stability. However, the assertion of its superiority over conventional suturing methods for ACLS necessitates substantiation through rigorous investigation via well-designed randomized controlled clinical trials.

Automated periodontitis bone loss diagnosis in panoramic radiographs using a bespoke two-stage detector.

Periodontitis is a serious oral disease that can lead to severe conditions such as bone loss and teeth falling out if left untreated. Diagnosis of radiographic bone loss (RBL) is critical for the staging and treatment of periodontitis. Unfortunately, the RBL diagnosis by examining the panoramic radiographs is time-consuming. The demand for automated image analysis is urgent. However, existing deep learning methods have limited performances in diagnosis accuracy and have certain difficulties in implementation. Hence, we propose a novel two-stage periodontitis detection convolutional neural network (PDCNN), where we optimize the detector with an anchor-free encoding that allows fast and accurate prediction. We also introduce a proposal-connection module in our detector that excludes less relevant regions of interests (ROIs), making the network focus on more relevant ROIs to improve detection accuracy. Furthermore, we introduced a large-scale, high-resolution panoramic radiograph dataset that captures various complex cases with professional periodontitis annotations. Experiments on our panoramic-image dataset show that the proposed approach achieved an RBL classification accuracy of 0.762. This result shows that our approach outperforms state-of-the-art detectors such as Faster R-CNN and YOLO-v4. We can conclude that the proposed method successfully improves the RBL detection performance. The dataset and our code have been released on GitHub. (https://github.com/PuckBlink/PDCNN).

TOP1 inhibition induces bifurcated JNK/MYC signaling that dictates cancer cell sensitivity.

Rationale: Triple-negative breast cancer (TNBC) does not respond to anti-estrogen and anti-HER2 therapies and is commonly treated by chemotherapy. TNBC has a high recurrence rate, particularly within the first 3 years. Thus, there is an urgent clinical need to develop more effective therapies for TNBC. Topoisomerase I (TOP1) inhibitors cause DNA damage, making these drugs desirable for TNBC treatment since DNA repair machinery is defective in this subtype of breast cancer. Among the main molecular subtypes of breast cancer, the TNBC cell lines exhibited the highest TOP1 inhibition sensitivity. However, clinically used TOP1 inhibitors, such as topotecan and irinotecan, have shown limited clinical applications and the reasons remain unclear. Understanding the mechanism of differential responses to TOP1 blockade and identifying the predictive markers for cancer cell sensitivity will help further TOP1-targeted therapy for TNBC treatment and improve the clinical use of TOP1 inhibitors. Methods: Viability assays were used to evaluate breast cancer cell sensitivity to topotecan and other TOP1 inhibitors as well as TOP2 inhibitors. An in vitro-derived topotecan-resistant TNBC cell model and TNBC xenograft models were employed to confirm cancer cell response to TOP1 blockade. RNA-seq was used to identify potential predictive markers for TNBC cell response to TOP1 blockade. Western blotting and qRT-PCR were performed to measure the protein levels and RNA expression. ATAC-seq and luciferase reporter assays were used to examine MYC transcriptional regulations. The effects of MYC and JNK in cancer cell response to TOP1 inhibition were validated via loss-of-function and gain-of-function experiments. Results: We observed two distinct and diverging cancer cell responses - sensitive versus resistant to TOP1 inhibition, which was confirmed by TNBC xenograft mouse models treated by topotecan. TNBC cells exhibited bifurcated temporal patterns of ATR pathway activation upon TOP1 inhibitor treatment. The sensitive TNBC cells showed an "up then down" dynamic pattern of ATR/Chk1 signaling, while the resistant TNBC cells exhibited a "persistently up" profile. On the contrary, opposite temporal patterns of induced expression of MYC, a key regulator and effector of DNA damage, were found in TNBC cells treated by TOP1 inhibitors. Mechanistically, we showed that TOP1-induced JNK signaling upregulated MYC expression. Furthermore, pharmacological inhibition of ATR reversed TNBC cell resistance to topotecan, whereas MYC knockdown and JNK inhibition reduced cancer cell sensitivity. Conclusions: Dynamic temporal profiles of induced ATR/Chk1 and JNK activation as well as MYC expression, may predict cancer cell response to TOP1 inhibitors. JNK activation-mediated constitutive elevation of MYC expression may represent a novel mechanism governing cancer cell sensitivity to TOP1-targeting therapy. Our results may provide implications for identifying TNBC patients who might benefit from the treatment with TOP1 inhibitors.

A New Compound with Increased Antitumor Activity by Cotargeting MEK and Pim-1.

Feedback circuits are one of the major causes underlying tumor resistance. Thus, compounds that target one oncogenic pathway with simultaneously blocking its compensatory pathway will be of great value for cancer treatment. Here, we develop a new MEK inhibitor designated as KZ-02 that exhibits unexpectedly higher cytotoxicity than its starting compound AZD6244, a well-known MEK inhibitor, in colorectal cancer (CRC). Subsequent kinase selectivity study identified Pim-1 as an additional cellular target for KZ-02. Further studies showed that AZD6244 and Pim-1 1 (a Pim-1 inhibitor) have a synergistic effect on CRC suppression. Mechanistic study revealed that MEK inhibition by AZD6244 leads to increased Pim-1 expression, which could be a general mechanism behind the compromised cell-killing activity of MEK inhibitors. KZ-02, despite increasing Pim-1 mRNA expression, simultaneously promotes Pim-1 proteasomal degradation. Therefore, we uncover a new MEK inhibitor KZ-02 with significantly enhanced antitumor activity by co-targeting MEK and Pim-1.