Biomechanical evaluation of three surgical scenarios of posterior lumbar interbody fusion by finite element analysis

BACKGROUND: For the treatment of low back pain, the following three scenarios of posterior lumbar interbody fusion (PLIF) were usually used, i.e., PLIF procedure with autogenous iliac bone (PAIB model), PLIF with cages made of PEEK (PCP model) or titanium (Ti) (PCT model) materiel. But the benefits or adverse effects among the three surgical scenarios were still not fully understood. METHOD: Finite element analysis (FEA), as an efficient tool for the analysis of lumbar diseases, was used to establish a three-dimensional nonlinear L1-S1 FE model (intact model) with the ligaments of solid elements. Then it was modified to simulate the three scenarios of PLIF. 10 Nm moments with 400 N preload were applied to the upper L1 vertebral body under the loading conditions of extension, flexion, lateral bending and torsion, respectively. RESULTS: Different mechanical parameters were calculated to evaluate the differences among the three surgical models. The lowest stresses on the bone grafts and the greatest stresses on endplate were found in the PCT model. The PCP model obtained considerable stresses on the bone grafts and less stresses on ligaments. But the changes of stresses on the adjacent discs and endplate were minimal in the PAIB model. CONCLUSIONS: The PCT model was inferior to the other two models. Both the PCP and PAIB models had their own relative merits. The findings provide theoretical basis for the choice of a suitable surgical scenario for different patients

Direct LED writing of submicron resist patterns : towards the fabrication of individually-addressable InGaN submicron stripe-shaped LED arrays

Submicron stripe-shaped InGaN light-emitting diode (LED) arrays with individually addressable capabilities are demonstrated. The critical submicronstripe metallic electrodes, which define the emission pattern, are formed by direct LED writing in a mask-free manner. The individually addressable submicron-stripe LEDs show excellent performance in terms of their electrical characteristics (with typical turn-on voltage of 3 V, operational stability and power output up to 28 μW at 3 mA). Unlike conventional broad-sized LEDs, the efficiency droop of the submicron-stripe LED is significantly suppressed-in fact, there is no efficiency droop for current densities up to 100 A/cm2. Furthermore, the submicron-stripe LED shows a lower temperature-dependent shift of the emission wavelength. The lateral emission width is increased with increasing injection current, resulting in a wider lateral emission size than the metallic submicron-stripe electrode. The underlying physics of these phenomena are analysed. Such submicron-stripe LED arrays open up promising applications in nanophotonics and bio-sensing

RFID-Based Indoor Spatial Query Evaluation with Bayesian Filtering Techniques

People spend a significant amount of time in indoor spaces (e.g., office buildings, subway systems, etc.) in their daily lives. Therefore, it is important to develop efficient indoor spatial query algorithms for supporting various location-based applications. However, indoor spaces differ from outdoor spaces because users have to follow the indoor floor plan for their movements. In addition, positioning in indoor environments is mainly based on sensing devices (e.g., RFID readers) rather than GPS devices. Consequently, we cannot apply existing spatial query evaluation techniques devised for outdoor environments for this new challenge. Because Bayesian filtering techniques can be employed to estimate the state of a system that changes over time using a sequence of noisy measurements made on the system, in this research, we propose the Bayesian filtering-based location inference methods as the basis for evaluating indoor spatial queries with noisy RFID raw data. Furthermore, two novel models, indoor walking graph model and anchor point indexing model, are created for tracking object locations in indoor environments. Based on the inference method and tracking models, we develop innovative indoor range and k nearest neighbor (kNN) query algorithms. We validate our solution through use of both synthetic data and real-world data. Our experimental results show that the proposed algorithms can evaluate indoor spatial queries effectively and efficiently. We open-source the code, data, and floor plan at https://github.com/DataScienceLab18/IndoorToolKit

Systematic immunohistochemical screening for mismatch repair and ERCC1 gene expression from colorectal cancers in China: Clinicopathological characteristics and effects on survival

Background: We performed a systematic screening of colorectal cancer (CRC) tissues to investigate whether mismatch repair (MMR) status and ERCC1 protein expression could be predictive of clinical outcomes for these patients following the recommendation of The Evaluation of Genomic Applications in Practice of Prevention (EGAPP). Methods: The expression of four MMR genes and ERCC1 were assessed by immunohistochemistry (IHC) from cancer tissue samples of 2233 consecutive CRC patients. Results: We observed that most CRC patients with a proficient MMR (pMMR) status tended to have simultaneous ERCC1 protein expression (P< 0.001). Stage III CRC patients with deficient MMR (dMMR) had higher prognoses than the same stage patients with pMMR (DFS: 74% vs 65%, P = 0.04;OS: 79% vs 69%, P = 0.04). Here, dMMR is also associated with poorer survival for stage II patients after chemotherapy (DFS: 66% vs 78%, P = 0.04). Stage II and III patients that were shown to express ERCC1 protein had higher DFS and OS than those that were deficient in expression (stage II, DFS: 83% vs 70%, P = 0.006;OS 85% vs 73%, P = 0.02. Stage III, DFS: 67% vs56%, P = 0.03;OS: 71% vs 57%, P = 0.04). Conclusions: Our results indicate that dMMR appeared to predictive of a survival benefit for stage III CRC patients. We also found the determination of ERCC1 expression to be useful for predicting DFS or OS for stage II and III CRC patients. In addition, the expression of MMR genes and ERCC1 showed a significant relationship

A relationship to survival is seen by combining the factors of mismatch repair status, tumor location and age of onset in colorectal cancer patients

Background: The progression of colorectal cancer (CRC) may differ depending on the location of the tumor and the age of onset of the disease. Previous studies also suggested that the molecular basis of CRC varies with tumor location, which could affect the clinical management of patients. Therefore, we performed survival analysis looking at different age groups and mismatch repair status (MMR) of CRC patients according to primary tumor location in an attempt to identify subgroups of CRC that might help in the prognosis of disease. Methods: A group of 2233 patients operated on to remove their CRC tumors were analyzed (521 with right colon cancer, 740 with left colon cancer and 972 with rectal cancer). The expression of four MMR genes was assessed by immunohistochemistry (IHC), independent of clinical criteria. From the data collected, a predictive model for overall survival (OS) could be constructed for some associations of tumor location and age of onset using Kaplan-Meier, logistic and Cox regression analysis. Results When tumor location was considered as the lone factor, we found no statistical difference in overall survival (OS) between right cancer (68%), left cancer (67%) or rectal cancer tumor locations (71%) (HR: 1.17, 95% CI (confidence interval): 0.97-1.43, P = 0.057). When age of onset was considered, middle age (40-59 years) and older (60-85 years) patients were found to have higher OS than younger onset cancer (20-39 years) patients (69% vs 71% vs 59%, HR: 1.07, 95% confidence interval (CI): 0.91-1.25, P = 0.008). When both age of onset and tumor location were considered in combination as disease factors, we found that the subgroup of patients with left colon cancer from middle age (69%) and older (67%) aged patients had higher OS than younger (54%) patients (HR: 0.89, 95% CI: 0.68-1.16, P = 0.048). However in patients with right colon cancers, we found no statistical difference is OS between younger, middle age or older grouped patients (60% vs 71% vs 67%, HR: 0.84, 95% CI: 0.61-1.16, P = 0.194). With regard to rectal located cancers, we found that younger (62%) and middle age (68) patients had lower OS than older (77%) patients (HR: 1.46, 95% CI: 1.13-1.88, P = 0.004). The rates of deficient MMR (dMMR) was 10.4%. We found no statistical difference in OS stratified by tumor locations. However, right colon cancer patients with dMMR (86%) had higher OS than those with proficient MMR (pMMR) (63%) (HR: 3.01, 95% CI: 1.82-4.97, P<0.001). Left colon cancer patients with dMMR (76%) also had higher OS than those with pMMR (66%) (HR: 1.67, 95% CI: 0.95-2.92, P = 0.01). Oppositely, rectal cancer patients with dMMR (60%) had lower OS than those pMMR (68%) (HR: 0.77, 95% CI: 0.51-1.17, P = 0.04). Conclusions: These data demonstrate that primary tumor location can be an important factor when considered along with age of onset for the prognosis of CRC. Primary tumor location is also an important factor to evaluate the predictive effect of MMR status for the prognosis of CRC

Plasma microRNA Profiles as a Potential Biomarker in Differentiating Adult-Onset Still's Disease From Sepsis

Adult-onset Still's disease (AOSD) is a systemic inflammatory disease characterized by cytokine storm. However, a diagnostic test for AOSD in clinical use is yet to be validated. The aim of our study was to identify non-invasive biomarkers with high specificity and sensitivity to diagnosis of AOSD. MicroRNA (miRNA) profiles in PBMC from new-onset AOSD patients without any treatment and healthy controls (HCs) were analyzed by miRNA deep sequencing. Plasma samples from 100 AOSD patients and 60 HCs were used to validated the expression levels of miRNA by qRT-PCR. The correlations between expression levels of miRNAs and clinical manifestations were analyzed using advanced statistical models. We found that plasma samples from AOSD patients showed a distinct miRNA expression profile. Five miRNAs (miR-142-5p, miR-101-3p, miR-29a-3p, miR-29c-3p, and miR-141-3p) were significantly upregulated in plasma of AOSD patients compared with HCs both in training and validation sets. We discovered a panel including 3 miRNAs (miR-142-5p, miR-101-3p, and miR-29a-3p) that can predict the probability of AOSD with an area under the receiver operating characteristic (ROC) curve of 0.8250 in training and validation sets. Moreover, the expression levels of 5 miRNAs were significantly higher in active AOSD patients compared with those in inactive patients. In addition, elevated level of miR-101-3p was found in AOSD patients with fever, sore throat and arthralgia symptoms; the miR-101-3p was also positively correlated with the levels of IL-6 and TNF-α in serum. Furthermore, five miRNAs (miR-142-5p, miR-101-3p, miR-29c-3p, miR-29a-3p, and miR-141-3p) expressed in plasma were significantly higher in AOSD patients than in sepsis patients (P &lt; 0.05). The AUC value of 4-miRNA panel (miR-142-5p, miR-101-3p, miR-29c-3p, and miR-141-3p) for AOSD diagnosis from sepsis was 0.8448, revealing the potentially diagnostic value to distinguish AOSD patients from sepsis patients. Our results have identified a specific plasma miRNA signature that may serve as a potential non-invasive biomarker for diagnosis of AOSD and monitoring disease activity