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Successful application of deep machine learning could reduce time-consuming and labor-intensive clinical work of calculating the amount of radiographic bone loss (RBL) in diagnosing and treatment planning for periodontitis. This study aimed to test the accuracy of RBL classification by machine learning.A total of 236 patients with standardized full mouth radiographs were included. Each tooth from the periapical films was evaluated by three calibrated periodontists for categorization of RBL and radiographic defect morphology. Each image was pre-processed and augmented to ensure proper data balancing without data pollution, then a novel multitasking InceptionV3 model was applied.The model demonstrated an average accuracy of 0.87 ± 0.01 in the categorization of mild ( 15%) or severe (≥ 15%) bone loss with fivefold cross-validation. Sensitivity, specificity, positive predictive, and negative predictive values of the model were 0.86 ± 0.03, 0.88 ± 0.03, 0.88 ± 0.03, and 0.86 ± 0.02, respectively.Application of deep machine learning for the detection of alveolar bone loss yielded promising results in this study. Additional data would be beneficial to enhance model construction and enable better machine learning performance for clinical implementation.Higher accuracy of radiographic bone loss classification by machine learning can be achieved with more clinical data and proper model construction for valuable clinical application.

The era of big data brings opportunities and challenges to developing new statistical methods and models to evaluate social programs or economic policies or interventions. This paper provides a comprehensive review on some recent advances in statistical methodologies and models to evaluate programs with high-dimensional data. In particular, four kinds of methods for making valid statistical inferences for treatment effects in high dimensions are addressed. The first one is the so-called doubly robust type estimation, which models the outcome regression and propensity score functions simultaneously. The second one is the covariate balance method to construct the treatment effect estimators. The third one is the sufficient dimension reduction approach for causal inferences. The last one is the machine learning procedure directly or indirectly to make statistical inferences to treatment effect. In such a way, some of these methods and models are closely related to the de-biased Lasso type methods for the regression model with high dimensions in the statistical literature. Finally, some future research topics are also discussed.

Background Anatomic repair of anterior talofibular ligament (ATFL) is used to manage chronic lateral ankle instability (CLAI). However, the optimal suture configuration used to repair the ATFL is not yet determined. It remains unclear whether suture configuration affects clinical outcomes in such patients. Purpose To compare the functional outcomes of all-inside arthroscopic ATFL repair using either a loop suture and or a free-edge suture configuration in CLAI patients. Study Design Cohort study; Level of evidence, 3. Methods This retrospective cohort study included 71 patients with CLAI who had undergone an all-inside arthroscopic ATFL repair procedure with either loop suture (n = 36) or free-edge suture (n = 35) from February 2016 to July 2018. Comparable pre-operatively, the Visual analogy score (VAS), American Orthopedic Foot and Ankle Society scoring system (AOFAS), Karlsson Ankle Functional Score (KAFS) scoring system, Anterior Talar Translation (ATT) and Active Joint Position Sense (AJPS) were used to evaluate postoperative ankle function. Results There were no postoperative wound complications, implant reactions, or neurological or vascular injuries. Postoperative hospitalization, VAS, AOFAS, KAFS, AJPS and the time of return to sport were similar between the loop suture group and free-edge suture group. Requiring a longer procedure time, patients with loop suture configuration achieved better ATT. Conclusion All-inside arthroscopic ATFL repair procedure for CLAI treatment provides better ATT and comparable functional outcomes when a loop suture configuration is used instead of a free-edge suture configuration. A statistical difference in ATT was observed. Given the relatively short follow-up, it is questionable whether this will have any clinical relevance.

This paper proposes a novel metaheuristic optimizer, named Colony Search Optimization Algorithm (CSOA). The algorithm mimics the social behavior of early humans. Early humans expanded their settlements in search of more livable places to live. In CSOA, the worst solution is used to escape from local optima. And the number of these redundant solutions’ updates is reduced to improve the performance of the algorithm. CSOA is tested with 26 mathematical optimization problems and 4 classical engineering optimization problems. The optimization results are compared with those of various optimization algorithms. The experimental results show that the CSOA is able to provide very competitive results on most of the tested problems. Then, a new effective method is provided for solving optimization problems.

The decision problems in the design and control of warehousing order picking process include layout design, storage assignment, routing, and order batching policies. Previous researches on layout design for pick-and-pass systems are not abundant. However, a pick-and-pass system is a commonly used approach because of the growth of e-commerce and the faster delivery of small and frequent orders. This paper presents an algorithm to determine the number of zones, and the number of picking bins and racks in each zones for the pick-and-pass systems such that both investment and operational costs can be minimized. A cycle time evaluation model is developed and incorporated into the proposed algorithm to aid a warehouse designer to quickly evaluate design alternatives for warehouse configurations. The result indicates that the cycle time evaluation model appears to be sufficiently accurate for practical purpose and the optimal layout can be determined by the proposed algorithm.

In Western countries, breast cancer tends to occur in older postmenopausal women. However, in Asian countries, the proportion of younger premenopausal breast cancer patients is increasing. Increasing evidence suggests that the gut microbiota plays a critical role in breast cancer. However, studies on the gut microbiota in the context of breast cancer have mainly focused on postmenopausal breast cancer. Little is known about the gut microbiota in the context of premenopausal breast cancer. This study aimed to comprehensively explore the gut microbial profiles, diagnostic value, and functional pathways in premenopausal breast cancer patients. Here, we analyzed 267 breast cancer patients with different menopausal statuses and age-matched female controls. The α-diversity was significantly reduced in premenopausal breast cancer patients, and the β-diversity differed significantly between breast cancer patients and controls. By performing multiple analyses and classification, 14 microbial markers were identified in the different menopausal statuses of breast cancer. Bacteroides fragilis was specifically found in young women of premenopausal statuses and Klebsiella pneumoniae in older women of postmenopausal statuses. In addition, menopausal-specific microbial markers could exhibit excellent discriminatory ability in distinguishing breast cancer patients from controls. Finally, the functional pathways differed between breast cancer patients and controls. Our findings provide the first evidence that the gut microbiota in premenopausal breast cancer patients differs from that in postmenopausal breast cancer patients and shed light on menopausal-specific microbial markers for diagnosis and investigation, ultimately providing a noninvasive approach for breast cancer detection and a novel strategy for preventing premenopausal breast cancer., Breast cancer: gut microbes before and after menopause Women developing breast cancer before the menopause have less diverse gut microbe populations than their healthy peers, and significantly different gut microbial profiles than postmenopausal breast cancer patients. There is increasing evidence of a link between gut microbes and breast cancer, but most studies have focused on women after the menopause. The incidence of breast cancer in premenopausal women is increasing, especially in Asia. Researchers in Taiwan led by Chih-Po Chiang at Kaohsiung Medical University Hospital compared gut microbial populations in 267 breast cancer patients at different menopausal stages to matched controls. The results suggest that gut microbe profiling might offer a novel and noninvasive method for diagnosing and monitoring breast cancer. It may also lead to new strategies for prevention and treatment, as evidence emerges of a link between gut microbes and cancer.

Parts made of zirconia ceramics have been used in various high-end fields, and some of these parts exhibit complex styles with various curved surfaces. As a prominent machining technique for manufacturing zirconia ceramic parts, tangential ultrasonic-assisted grinding has mainly been employed in improving the processing efficiency and simultaneously ensuring the surface quality. With the aim of further improving the processing performance of tangential ultrasonic-assisted curved surface grinding, the effects of the grinding paths with α = 0°, α = 45°, and α = 90° on the surface quality and profile of a workpiece were studied for a specific curved surface, and the wear of the grinding wheel with different paths was analyzed. In addition, the material removal mechanisms were discussed for single diamond grit grinding tests. The obtained results demonstrated that (1) the surface roughness Sa was different at different grinding paths, i.e., at different values of α, and the surface finish mainly depended on the ultrasonic amplitude. (2) The profile error of the curved work-surface was different at different values of α. (3) The wear of the grinding wheel at α = 45° was the most serious, and at α = 0° and α = 90°, the abrasive grain wear was slight. These tendencies agreed with the case of the work-surface quality. (4) The material removal mechanism was different with and without ultrasonics, which resulted in the differences in the work-surface finish.

Stroke has become the second leading cause of death in people aged higher than 60 years, with cancer being the first. Intracerebral hemorrhage (ICH) is the most lethal type of stroke. Using imaging techniques to evaluate the evolution of intracranial hematomas in patients with hemorrhagic stroke is worthy of ongoing research. The difficulty in obtaining ultra-early imaging data and conducting intensive dynamic radiographic imaging in actual clinical settings has led to the application of experimental animal models to assess the evolution of intracranial hematomas. Herein, we review the current knowledge on primary intracerebral hemorrhage mechanisms, focus on the progress of animal studies related to hematoma development and secondary brain injury, introduce preclinical therapies, and summarize related challenges and future directions.

Transsphenoidal surgery (TSS) is the first-line treatment for patients with Cushing's disease (CD). However, the reported remission rates of patients who received TSS vary widely between different studies, and the predictors of surgical outcomes remain controversial. The present study analyzed the early outcome of TSS in a large population of patients with CD at a single center, and identified potential predictors of initial remission of TSS in patients with CD.The clinical features and surgical outcomes of CD patients who underwent TSS between 1988 and 2018 at Peking Union Medical College Hospital (PUMCH) were collected and analyzed from their medical records.Of the 1604 CD patients who underwent TSS at PUMCH between February 1988 and October 2018, 1106 patients had complete medical data and pathological results. After surgery, the overall postoperative initial remission rate was 72.5, and 27.5% of patients maintained persistent hypercortisolism. The initial remission rate of patients with preoperative noninvasive adenoma based on MRI (77.1%), intraoperative noninvasiveness (72.5%), microadenoma (74.3%), pathological confirmation (76.4%), and first TSS (73.9%) was significantly higher than that in patients with preoperative invasive adenoma (53.0%), intraoperative invasiveness (60.7%), macroadenomas (65.9%), pathologically negative (49.7%), and repeat TSS (56.0%), respectively (all P 0.05). The initial remission rate in patients with pseudocapsule-based extracapsular resection (88.1%), MRI-visible adenoma (74.2%) was higher than that in patients without pseudocapsule-based extracapsular resection (77.1%), and with MRI-negative results (64.5%), respectively, but did not reach statistical significance (All P 0.05). Striking, there was no significant differences in initial remission rates between patients who underwent selective adenomectomy and enlarged adenomectomy (P 0.05). Whereas, the initial remission rates in patients who underwent partial hypophysectomy only was 51.0%, which was much lower than that in patients underwent selective adenomectomy and enlarged adenomectomy (P 0.05).The TSS is a safe and effective procedure for the treatment of CD. Whereas, preoperative invasiveness based on MRI, intraoperative invasiveness, macroadenomas pathologically negative, and repeat TSS are related to lower initial remission rates.

This paper investigates the time-varying formation tracking (TVFT) problem of multiple heterogeneous Euler–Lagrange agents (MHELAs) with predefined-time convergence ability under directed interaction topology, where both the parametric uncertainties and external disturbances are taken into account. A new predefined-time hierarchical control (PTHC) algorithm is designed to solve the aforementioned challenging problem. Specifically, the TBG-based distributed estimator algorithm utilizing the time base generator (TBG) is firstly designed to estimate the states of the virtual leader in a predefined time. Besides, based on the obtained estimators, the predefined-time controller is presented to accomplish the robust time-varying formation tracking of the MHELAs in the local control layer. By employing the Lyapunov and Lagrange stability theory, the sufficient conditions for achieving the desired performance of the MHELAs are derived. Eventually, numerical simulations are performed to illustrate that the aforementioned theoretical results for MHELAs are effective.

Buton rock asphalt (BRA) is used as a modifier in road applications to enhance the performance of asphalt pavement mixtures. Rock-modified sand–asphalt (RMSA) concrete can be prepared by adding BRA to sand–asphalt (SA) concrete. In this study, BRA was added to SA concrete through wet and dry modification processes. In the dry modification process, BRA was directly added to SA concrete. In the wet modification process, pure rock asphalt (PRA) extracted from BRA was preblended with the base asphalt of SA concrete. We evaluated the engineering properties of RMSA concrete through comprehensive laboratory tests. The comparison and control groups comprised RMSA concrete and polymer-modified sand–asphalt (PMSA) concrete. The test results indicated that the Marshall stability and indirect tensile strength of RMSA were higher than those of the unmodified sand–asphalt (USA) concrete and PMSA concrete. Regarding durability, the index of retained strength (IRS) and tensile strength ratio (TSR) of RMSA were higher than those of PMSA. Thus, adding BRA to SA concrete can improve its moisture damage resistance and durability. The dynamic stability (DS) of RMSA was higher than that of USA concrete and close to that of PMSA. Overall, BRA was found to be suitable for use in conjunction with SA concrete. We recommended that the PRA content should not exceed 15% by weight of the rock-modified asphalt binder. The addition of BRA improved the mechanical properties, moisture damage resistance, permanent deformation resistance, and high-temperature performance of RMSA. The feasibility of BRA addition to SA concrete was validated.

Objective To investigate the role of NudCD1 in spindle assembly checkpoint regulation and in the prognosis of colorectal cancer. Methods Immunohistochemical staining was used to detect in situ expression of NudCD1 in 100 colorectal cancer tissue samples. A chi-square test was used to analyse the correlation between the NudCD1 protein expression level of the cancer tissues and clinicopathological features. The Kaplan–Meier survival analysis was used to assess the correlation between the NudCD1 mRNA expression and the three-year survival of patients with colorectal cancer. The impact of NudCD1 on the development of colorectal cancer and the underlying molecular mechanisms were assessed by flow cytometry cell cycle and apoptosis assays after lentiviral overexpression of NudCD1 in two colorectal cancer cell lines. Quantitative real-time PCR was used to assess mRNA expression of the cellular spindle assembly checkpoint genes BUB1, BUBR1, MAD1, CDC20 and MPS1, as well as the downstream genes LIS1, DYNC1H1, and DYNLL1 in the NudC/LIS1/dynein pathway. Results Compared with normal intestinal tissue (8.00% with high expression), the expression of NudCD1 protein in colorectal cancer tissue was significantly higher (58.00% with high expression, P P P P P Conclusion NudCD1 can serve as a valuable prognostic marker for colorectal cancer. It may be involved in the regulation of spindle-assembly checkpoint-gene expression and the LIS1 pathway of colorectal cancer cells.

Taking into account the spatial diffusion effect, this paper deals with the stability problem of genetic regulatory networks with both time-varying discrete delays (DDs) and distributed delays (DTDs). By virtue of the theories of delayed partial differential equation and Lyapunov stability, new algebraic conditions are established to guarantee the global exponential stability of the genetic regulatory networks with spatial diffusion (SDGRNs) with time-varying hybrid delays. The obtained conditions are generalized and easily calculated based on the system parameters. Besides, some extended results are presented for SDGRNs without diffusion effect or DTDs. Finally, the effectiveness and feasibility of the theoretical results are illustrated by two numerical examples and the corresponding simulation results.

Oxidative stress and neuroinflammatory response after the ischemic injury are important pathophysiologic mechanisms that cause brain tissue loss and neurological deficit. This study aims to observe the expression and role of carbonyl reductase 1 (CBR1), an NADPH-dependent oxidoreductase with specificity for carbonyl compounds such as 4-hydroxynonenal (4-HNE), in the brain after ischemic injury and to investigate the influence of CBR1 on ischemia-induced neuroinflammation. CBR1 expresses in the neurons, astrocyte, and microglia in the normal brain. The expression of CBR1 decreased in the ischemic regions following cerebral ischemia, and also reduced in primary neurons after OGD (oxygen-glucose deprivation); however, the expression of CBR1 significantly increased in microglia in the ischemic penumbra. Furthermore, TAT-CBR1 fusion protein played neuroprotective effects in reducing the infarct volume and improving neurological outcomes after ischemic injury. Mechanistically, CBR1 decreased the levels of 4-HNE in the brain after stroke; it also modulated microglial polarization toward the M2 phenotype, which was well-known to confer neuroprotection after ischemic injury. Our results demonstrate that CBR1 provides neuroprotection against ischemic injury by reducing oxidative stress and neuroinflammation, making a promising agent for cerebral ischemia treatment.