Efficacy of PE-PLIF with a novel ULBD approach for lumbar degeneration diseases: a large-channel endoscopic retrospective study.

PURPOSE: This study aims to assess the effectiveness of Percutaneous Endoscopic Posterior Lumbar Interbody Fusion (PE-PLIF) combined with a novel Unilateral Laminotomy for Bilateral Decompression (ULBD) approach using a large-channel endoscope in treating Lumbar Degenerative Diseases (LDD). METHODS: This retrospective analysis evaluates 41 LDD patients treated with PE-PLIF and ULBD from January 2021 to June 2023. A novel ULBD approach, called 'Non-touch Over-Top' technique, was utilized in this study. We compared preoperative and postoperative metrics such as demographic data, Visual Analogue Scale (VAS) for pain, Oswestry Disability Index (ODI), Japanese Orthopedic Association (JOA) score, surgical details, and radiographic changes. RESULTS: The average follow-up duration was 14.41 ± 2.86 months. Notable improvements were observed postoperatively in VAS scores for back and leg pain (from 5.56 ± 0.20 and 6.95 ± 0.24 to 0.20 ± 0.06 and 0.12 ± 0.05), ODI (from 58.68 ± 0.80% to 8.10 ± 0.49%), and JOA scores (from 9.37 ± 0.37 to 25.07 ± 0.38). Radiographic measurements showed significant improvements in lumbar and segmental lordosis angles, disc height, and spinal canal area. A high fusion rate (97.56% at 6 months, 100% at 12 months) and a low cage subsidence rate (2.44%) were noted. CONCLUSIONS: PE-PLIF combined with the novel ULBD technique via a large-channel endoscope offers significant short-term benefits for LDD management. The procedure effectively expands spinal canal volume, decompresses nerve structures, improves lumbar alignment, and stabilizes the spine. Notably, it improves patients' quality of life and minimizes complications, highlighting its potential as a promising LDD treatment option.

Effect and Safety of Herbal Medicine Foot Baths in Patients with Diabetic Peripheral Neuropathy: A Multicenter Double-Blind Randomized Controlled Trial.

OBJECTIVE: To evaluate the effect and safety of foot baths with Tangbi Waixi Decoction (TW) in treating patients with diabetic peripheral neuropathy (DPN). METHODS: It is a multicenter double-blinded randomized controlled trial. Participants with DPN were recruited between November 18, 2016 and May 30, 2018 from 8 hospitals in China. All patients received basic treatments for glycemic management. Patients received foot baths with TW herbal granules either 66.9 g (intervention group) or 6.69 g (control group) for 30 min once a day for 2 weeks and followed by a 2-week rest, as a therapeutic course. If the Toronto Clinical Scoring System total score (TCSS-TS) ⩾6 points, the patients received a total of 3 therapeutic courses (for 12 weeks) and were followed up for 12 weeks. The primary outcome was change in TCSS-TS score at 12 and 24 weeks. Secondary outcomes included changes in bilateral motor nerve conduction velocity (MNCV) and sensory nerve conduction velocity (SNCV) of the median and common peroneal nerve. Safety was also assessed. RESULTS: Totally 632 patients were enrolled, and 317 and 315 were randomized to the intervention and control groups, respectively. After the 12-week intervention, patients in both groups showed significant declines in TCSSTS scores, and significant increases in MNCV and SNCV of the median and common peroneal nerves compared with pre-treatment (P<0.05). The reduction of TCSS-TS score at 12 weeks and the increase of SNCV of median nerve at 24 weeks in the control group were greater than those in the intervention group (P<0.05). The number of adverse events did not differ significantly between groups (P>0.05), and no serious adverse event was related with treatment. CONCLUSION: Treatment of TW foot baths was safe and significantly benefitted patients with DPN. A low dose of TW appeared to be more effective than a high dose. (Registry No. ChiCTR-IOR-16009331).

AIS-based operational phase identification using Progressive Ablation Feature Selection with machine learning for improving ship emission estimates.

The work status of ships' engines and boilers has a significant impact on emission estimates, which are closely related to ships' operational phases. To improve the accuracy of emission estimates, this study proposed a machine learning-based classification model for identifying operational phases. We proposed 12 operational phase relevance features by analyzing motion behavior-related and geospatial characteristics-related features from the Automatic Identification System (AIS) data from the two bulk carriers. The random forest (RF) model showed the best performance in identifying one of the bulk carrier's operational phases among the five machine models, with the accuracy, F1score and Area Under Curve (AUC) of 96.66%, 93.34% and 99.93%, respectively. By adopting the Progressive Ablation Feature Selection (PAFS) method with RF, the number of features was reduced from 12 to 8, and the accuracy (96.38%), F1score (92.70%), and AUC (98.81%) were almost same with that obtained from all 12 features. Additionally, the effectiveness of the RF model was validated on the other bulk carriers. Compared with the traditional algorithms, the RF model showed better performance in ship operational phase identification and improved the average accuracy of NOx emission estimation for the main engine and auxiliary engine by 57.83% and 93.89%, respectively, under different operational phases. These results provide the basis for port traffic management and ship emission control.Implications: A new ship operational phase identification approach was proposed in this study. If the proposed approach is adopted by International Maritime Organization, it will improve the accuracy of ship emission estimates and bring new insights into global shipping greenhouse gas (GHG) emissions and their impact on global change. The port authorities could benefit from the proposed approach, which can be extended to ship types with similar behavior to bulk carriers, such as containers and general cargoes. This can reveal patterns of ship behavior in specific areas, which helps to identify potential collision risks, channel blockages, and other safety issues and take appropriate management measures to ensure the safe operation of the port. The proposed approach can help shipping companies to accurately estimate the GHG emissions of their fleets and to accurately predict carbon tax costs. Base on that, carbon emissions and carbon tax burden can be reduced by adopting corresponding management control measures.

Mutation Endmember Library Sparse Mixed Abundance Estimation Model for Glioma Margin Determination with Raman Spectroscopy.

The glioma margin is a region of brain tissue where glioblastoma tissue transitions to normal tissue with varying levels of cancer cell concentration. This article uses Raman spectroscopy to detect the glioma margin, which is a fuzzy and uncertain substance that cannot be accurately identified by conventional pattern recognition algorithms. This article applies abundance estimation to Raman spectral unmixing of glioma marginal tissues for the accurate and real-time determination of the tumor surgical boundary during an operation. This article introduces a novel method: the mutation endmember library sparse mixed abundance estimation model. This method adds different representative Raman spectra to each endmember library to account for its dynamic properties, thus reducing errors from such variations and fully capturing the diversity within the substance. Moreover, it uses group sparse endmember bundle decomposition, where each substance endmember library consists of multiple Raman spectra. Fractionally mixed norms are used to ensure intergroup and intragroup sparsity, eliminate redundant spectra, and enhance the generalization ability of the abundance estimation. This method was compared with conventional abundance estimation methods. The experimental results of 112 human glioma margin tissues demonstrate that this method outperforms other methods in terms of accuracy, stability, and generalization ability. This article demonstrates the potential of miniature Raman spectroscopy as a new approach to in vivo and noninvasively determining intraoperative margin assessment.

The efficacy and safety of ultrasonic bone scalpel for removing retrovertebral osteophytes in anterior cervical discectomy and fusion: A retrospective study.

In this study, we present a novel surgical method that utilizes the ultrasonic bone scalpel (UBS) for the removal of large retrovertebral osteophytes in anterior cervical discectomy and fusion (ACDF) and evaluate its safety and efficacy in comparison to the traditional approach of using high-speed drill (HSD). A total of 56 patients who underwent ACDF for retrovertebral osteophytes were selected. We recorded patients' baseline information, operation time, intraoperative blood loss, complications, JOA and VAS scores, and other relevant data. The mean operation time and the mean intraoperative blood loss in the UBS group were less than those in the HSD group (P < 0.05). Although both groups exhibited considerable improvements in JOA and VAS scores following surgery, there was no statistically significant difference between the two groups (P > 0.05). Additionally, no significant disparities were found in bone graft fusion between the two groups at 6- and 12-months postsurgery. Notably, neither group exhibited complications such as dura tear or spinal cord injury. Our study found that the use of UBS reduced operative time, minimized surgical bleeding, and led to clinical outcomes comparable to HSD in ACDF. This technique offers an effective and safe method of removing large retrovertebral osteophytes.

Dynamic Multivariate Outlier Detection Algorithm Using Ultraviolet Visible Spectroscopy for Monitoring Surface Water Contamination With Hydrological Fluctuation in Real-Time.

The contamination of surface water is of great harm. Ultraviolet-visible (UV-Vis) spectroscopy is an effective method to detect water contamination. However, surface water quality is influenced by hydrological fluctuation caused by rain, change of flow, etc., leading to changes of spectral characteristics over time. In the process of contamination detection, such changes cause confusion between hydrological fluctuation spectra and contaminated water spectra, thus increasing the false alarm rate. Besides, missing alarms of contaminated water is a common problem when the signal-to-noise ratio is low. In this paper, a dynamic multivariable outlier sampling rate detection (DM-SRD) algorithm is proposed. A dynamic updating strategy is introduced to increase adaptability to hydrological fluctuation. Additionally, multiple outlier variables are adopted as outlying degree indicators, which increases the accuracy of contamination detection. Two experiments were carried out using spectra collected from real surface water sites and hydrological fluctuation was constructed. To verify the effectiveness of the DM-SRD method, a comparison with the static SRD method and spectral match method was conducted. The results show that the accuracy of the DM-SRD method is 97.8%. Compared with the other two detection methods, DM-SRD significantly reduces false alarm rate and avoids missing alarms. Additionally, the results demonstrate that whether the database contained prior information on hydrological fluctuation or not, DM-SRD maintained high detection accuracy, which indicates great adaptability and robustness.

N6-methyladenosine (m6A) in cancer therapeutic resistance: Potential mechanisms and clinical implications.

Cancer therapy resistance (CTR) is the development of cancer resistance to multiple therapeutic strategies, which severely affects clinical response and leads to cancer progression, recurrence, and metastasis. N6-methyladenosine (m6A) has been identified as the most common, abundant, and conserved internal transcriptional alterations of RNA modifications, regulating RNA splicing, translation, stabilization, degradation, and gene expression, and is involved in the development and progression of a variety of diseases, including cancer. Recent studies have shown that m6A modifications play a critical role in both cancer development and progression, especially in reversing CTR. Although m6A modifications have great potential in CTR, the specific molecular mechanisms are not fully elucidated. In this review, we summarize the potential molecular mechanisms of m6A modification in CTR. In addition, we update recent advances in natural products from Traditional Chinese Medicines (TCM) and small-molecule lead compounds targeting m6A modifications, and discuss the great potential and clinical implications of these inhibitors targeting m6A regulators and combinations with other therapies to improve clinical efficacy and overcome CTR.

A new strategy for treating colorectal cancer: Regulating the influence of intestinal flora and oncolytic virus on interferon.

Colorectal cancer (CRC) has the third highest incidence and the second highest mortality in the world, which seriously affects human health, while current treatments methods for CRC, including systemic therapy, preoperative radiotherapy, and surgical local excision, still have poor survival rates for patients with metastatic disease, making it critical to develop new strategies for treating CRC. In this article, we found that the gut microbiota can modulate the signaling pathways of cancer cells through direct contact with tumor cells, generate inflammatory responses and oxidative stress through interactions between the innate and adaptive immune systems, and produce diverse metabolic combinations to trigger specific immune responses and promote the initiation of systemic type I interferon (IFN-I) and anti-viral immunity. In addition, oncolytic virus-mediated immunotherapy for regulating oncolytic virus can directly lyse tumor cells, induce the immune activity of the body, interact with interferon, inhibit the anti-viral effect of IFN-I, and enhance the anti-tumor effect of IFN-II. Interferon plays an important role in the anti-tumor process. We put forward that exploring the effects of intestinal flora and oncolytic virus on interferon to treat CRC is a promising therapeutic option.

Nephrotoxicity assessment of podophyllotoxin-induced rats by regulating PI3K/Akt/mTOR-Nrf2/HO1 pathway in view of toxicological evidence chain (TEC) concept.

Adverse reactions to traditional Chinese medicine have hindered the healthy development and internationalization process of the traditional Chinese medicine industry. The critical issue that needs to be solved urgently is to evaluate the safety of traditional Chinese medicine systematically and effectively. Podophyllotoxin (PPT) is a highly active compound extracted from plants of the genus Podophyllum such as Dysosma versipellis (DV). However, its high toxicity and toxicity to multiple target organs affect the clinical application, such as the liver and kidney. Based on the concurrent effects of PPT's medicinal activity and toxicity, it would be a good example to conduct a systematic review of its safety. Therefore, this study revolves around the Toxicological Evidence Chain (TEC) concept. Based on PPT as the main toxic constituent in DV, observe the objective toxicity impairment phenotype of animals. Evaluate the serum biochemical indicators and pathological tissue sections for substantial toxic damage results. Using metabolomics, lipidomics, and network toxicology to evaluate the nephrotoxicity of PPT from multiple perspectives systematically. The results showed that PPT-induced nephrotoxicity manifested as renal tubular damage, mainly affecting metabolic pathways such as glycerophospholipid metabolism and sphingolipid metabolism. PPT inhibits the autophagy process of kidney cells through the PI3K/Akt/mTOR and Nrf2/HO1 pathways and induces the activation of oxidative stress in the body, thereby causing nephrotoxic injury. This study fully verified the feasibility of the TEC concept for the safety and toxicity evaluation of traditional Chinese medicine. Provide a research template for systematically evaluating the safety of traditional Chinese medicine.

The γδ T cells dual function and crosstalk with intestinal flora in treating colorectal cancer is a promising area of study.

The occurrence of colorectal cancer (CRC) is highly prevalent and severely affects human health, with the third-greatest occurrence and the second-greatest rate of death globally. Current CRC treatments, including surgery, radiotherapy, and chemotherapy, do not significantly improve CRC patients' survival rate and quality of life, so it is essential to develop new treatment strategies. Adoptive cell therapy and other immunotherapy came into being. Currently, there has been an especially significant emphasis on γδ T cells as being the primary recipient of adoptive cell therapy. The present investigation found that γδ T cells possess the capability to trigger cytotoxicity in CRC cells, secrete cytokines, recruit immune cells for the purpose of destroying cancer cells, and inhibit the progress of CRC indirectly. Nevertheless, It is possible for γδ T cells to initiate a storm of inflammatory factors and inhibit the immune response to promote the advancement of CRC. This review demonstrates a close association between the γδ T cell initiation pathway and their close association with the intestinal flora. It has been observed that the intestinal flora performs a vital function in facilitating the stimulation and functioning of γδ T cells. The tumor-fighting effect is mainly regulated by desulphurizing Vibrio and lactic acid bacteria. In contrast, the regulation of tumor-promoting impact is closely related to Clostridia and ETBF. This review systematically combs γδ T cell dual function and their relationship to intestinal flora, which offers a conceptual framework for the γδ T cell application for CRC therapies.

The effectiveness of postoperative rehabilitation interventions that include breathing exercises to prevent pulmonary atelectasis in lung cancer resection patients: a systematic review and meta-analysis.

BACKGROUND: The main aim of this systematic review was to determine the effectiveness of postoperative rehabilitation interventions that include breathing exercises as a component to prevent atelectasis in lung cancer resection patients. METHODS: In this review, we systematically and comprehensively searched the Cochrane Library, PubMed, EMBASE, and Web of Science in English and CNKI and Wanfang in Chinese from 2012 to 2022. The review included any randomized controlled trials focusing on the effectiveness of postoperative rehabilitation interventions that include breathing exercises to prevent pulmonary atelectasis in lung cancer patients. Participants who underwent anatomic pulmonary resection and received postoperative rehabilitation interventions that included breathing exercises as a component were included in this review. The study quality and risks of bias were measured with the GRADE and Cochrane Collaboration tools, and statistical analysis was performed utilizing RevMan 5.3 software. RESULTS: The incidence of atelectasis was significantly lower in the postoperative rehabilitation intervention group (OR = 0.35; 95% CI, 0.18 to 0.67; I2 = 0%; P = 0.67) than in the control group. The patients who underwent the postoperative rehabilitation program that included breathing exercises (intervention group) had higher forced vital capacity (FVC) scores (MD = 0.24; 95% CI, 0.07 to 0.41; I2 = 73%; P = 0.02), forced expiratory volume in one second (FEV1) scores (MD = 0.31; 95% CI, 0.03 to 0.60; I2 = 98%; P < 0.01) and FEV1/FVC ratios (MD = 9.09; 95% CI, 1.50 to 16.67; I2 = 94%; P < 0.01). CONCLUSION: Postoperative rehabilitation interventions that included breathing exercises decreased the incidence rate of atelectasis and improved lung function by increasing the FVC, FEV1, and FEV1/FVC ratio.

Raman spectral pattern recognition of breast cancer: A machine learning strategy based on feature fusion and adaptive hyperparameter optimization.

Raman spectroscopy, as a kind of molecular vibration spectroscopy, provides abundant information for measuring components and molecular structure in the early detection and diagnosis of breast cancer. Currently, portable Raman spectrometers have simplified and made equipment application more affordable, albeit at the cost of sacrificing the signal-to-noise ratio (SNR). Consequently, this necessitates a higher recognition rate from pattern recognition algorithms. Our study employs a feature fusion strategy to reduce the dimensionality of high-dimensional Raman spectra and enhance the discriminative information between normal tissues and tumors. In the conducted random experiment, the classifier achieved a performance of over 96% for all three average metrics: accuracy, sensitivity, and specificity. Additionally, we propose a multi-parameter serial encoding evolutionary algorithm (MSEA) and integrate it into the Adaptive Local Hyperplane K-nearest Neighbor classification algorithm (ALHK) for adaptive hyperparameter optimization. The implementation of serial encoding tackles the predicament of parallel optimization in multi-hyperparameter vector problems. To bolster the convergence of the optimization algorithm towards a global optimal solution, an exponential viability function is devised for nonlinear processing. Moreover, an improved elitist strategy is employed for individual selection, effectively eliminating the influence of probability factors on the robustness of the optimization algorithm. This study further optimizes the hyperparameter space through sensitivity analysis of hyperparameters and cross-validation experiments, leading to superior performance compared to the ALHK algorithm with manual hyperparameter configuration.

Automated Synthesis and Preclinical Evaluation of Optimized Integrin α6-Targeted Positron Emission Tomography Imaging of Pancreatic Cancer.

Integrin α6 has been considered a promising biomarker, is overexpressed in many tumors, and plays a vital role in tumor formation, recurrence, and metastasis. In this study, we identified a novel high-affinity integrin α6-targeted peptide named RD2 (Arg-Trp-Tyr-Asp-PEG4)2-Lys-Lys and developed a 18F-radiolabeled peptide tracer ([18F]-AlF-NOTA-RD2) and evaluated its potential application in positron emission tomography (PET) imaging of pancreatic cancer. [18F]-AlF-NOTA-RD2 was produced using GMP (Good Manufacturing Practice of Medical Products)-compliant automatic radiosynthesis on a single GE FASTLab2 cassette-type synthesis module. The stability of [18F]-AlF-NOTA-RD2 was analyzed in phosphate-buffered saline (PBS) and fetal bovine serum (FBS). The cell uptake assay of the tracer was assessed using PANC-1 cells. In addition, small-animal PET imaging and biodistribution studies of [18F]-AlF-NOTA-RD2 were performed in pancreatic cancer subcutaneous tumor-bearing mice. The PET tracer [18F]-AlF-NOTA-RD2 was obtained with a radiochemical yield of 23.7 ± 4.7%, radiochemical purity of >99%, and molar activity of 165.7 ± 59.1 GBq/µmol. [18F]-AlF-NOTA-RD2 exhibited good in vitro stability in PBS and FBS. LogP octanol water value for the tracer was -2.28 ± 0.05 (n = 3). The binding affinity of RD2 to the integrin α6 protein (Kd = 0.13 ± 3.65 µM, n = 3) was significantly higher than that of the RWY (CRWYDENAC) (Kd = 6.97 ± 1.44 µM, n = 3). Small-animal PET imaging and biodistribution also revealed that [18F]-AlF-NOTA-RD2 displayed rapid and good tumor uptake and lower liver background uptake in PANC-1 tumor-bearing mice. [18F]-AlF-NOTA-RD2 showed significant radioactivity accumulation in tumors and was successfully blocked by NOTA-RD2. Compared with [18F]-FDG, [18F]-AlF-NOTA-RD2 PET imaging and biodistribution studies in PANC-1 xenograft tumor-bearing mice confirmed a good tumor-to-muscle ratio (8.69 ± 2.03 vs 1.41 ± 0.23, respectively) at 0.5 h and (2.99 ± 3.02 vs 1.43 ± 0.17, respectively) at 1 h post injection. Autoradiography of human pancreatic cancer tumor tissues further confirmed high accumulation of [18F]-AlF-NOTA-RD2. In summary, we developed an optimized integrin α6-targeted imaging tracer and obtained high radioactivity products with a cassette-type synthesis module; moreover, the tracer exhibited good binding affinity with integrin α6 and good target specificity for PANC-1 cells in xenograft pancreatic tumor-bearing mice, demonstrating its promising application as a noninvasive PET radiotracer of integrin α6 expression in pancreatic cancer.

An outlier detection algorithm based on segmentation and pruning of competitive network for glioma identification using Raman spectroscopy.

Raman spectroscopy is a promising diagnostic tool for brain gliomas, owing to its non-invasive and high information density properties. However, identifying patterns in glioma cancer tissue and healthy tissue in the brain is challenging, and outlier spectra resulting from operator error or changes in external conditions can compromise the model's robustness and generalizability to new data. Given the heterogeneity of glioma tissue, the within-group variance of data obtained by a portable Raman spectrometer is relatively high, and inconsistencies in instrument repeatability and experimental conditions can lead to an incompact distribution of non-outlier points, complicating outlier detection. Strict outlier criteria may result in the deletion of non-outlier points, leading to reduced sample utilization. To address these issues, we propose the SPCN outlier detection algorithm, which segments and prunes a competitive network to extract global outlier features, identifies topological errors, and divides initial outlier domains using the α-ß region segmentation method. The algorithm also proposes a two-stage pruning method based on the characteristics of the manifold map and visualizes the outlier measure using a normalized histogram. Compared to traditional methods, SPCN is label-free and does not require an estimation of outlier distance threshold or data distribution density. We compared the accuracy of six outlier detection algorithms using Raman spectra collected from brain glioma tissues of 113 patients and examined changes in pattern recognition accuracy after removing the outliers, confirming the precision and robustness of SPCN. This method has the potential to enhance the accuracy and reliability of glioma diagnosis via Raman spectroscopy and can also be applied to outlier detection in other spectra such as near infrared and middle infrared.

Seasonal dynamics of coastal pollution migration in open waters with intensive marine ranching.

Mariculture activities have been recognized as one of the major sources of contamination for marine pollutants, such as the excessive discharging of nitrogen and phosphate. The fully understanding of the pollutants emission and transportation is crucial for coastal environment management. However, the influence of such highly dynamic coastal process on the pollutant migration remain unclear, such as the effects of coastal seasonal hydrodynamics on the dissolved pollutant transportation, especially under intensive marine ranching activities in open waters. This study investigated the seasonal transport mechanisms of pollutants released from three typical mariculture methods (floating raft, cage and bottom pond) in the Wangjia Island (WJ), Yellow Sea, China. We have conducted three field surveys to monitor the coastal dynamics and measure the distribution of dissolved pollutants in the ranching area. Results from these field surveys show that the WJ and adjacent area experienced significant degradation in terms of water quality with the development of regional marine ranching. The average of calculated index for eutrophication Ei increases from 0.12 in the non-farming area to 0.78 in the farming area. In order to delineate the impacts area of pollutant transport associated with these highly dynamics of water exchange, a Eulerian passive tracer-tracking module is applied to simulate the pollutant transport processes based on a field scale three-dimensional Finite Volume Coastal Ocean Model (FVCOM). Then after, the impacts of barotropic and baroclinic coastal dynamics on the migration of dissolved pollutants were evaluated. The transport of pollutants was greatly influenced by the different farming modes. The travel distance of pollutants released from the bottom pond farming mode was limited, whereas pollutants from the surface-farming methods were transported over a longer distance. In this study, there are three folders of finding: 1) The migration direction varies with seasons, with a landward direction in winter and an offshore direction in summer; 2) In winter, strong wind (wind speed over 10 m/s) is the dominant factor for water exchange, which is conducive to the dispersion of pollutants in the study area. However, in summer, the thermal stratification controls pollutant migration; 3) The results of breakthrough time illustrate that the pollutants travelled slower during summer, especially for pollutants discharged from the bottom pond farming method. In summary, this study demonstrates that even in open waters with stronger water exchange capacity, the pollutants from intensive marine ranching can still increase the risk of eutrophication. The finding of this study has important implications for the management and regulation of offshore aquaculture activities, particularly for mitigating pollutants from marine ranching.

Synergistic contribution of metal-acid sites in selective hydrodeoxygenation of biomass derivatives over Cu/CoOx catalysts.

The efficient hydrodeoxygenation (HDO) of biomass derivatives to yield specific products is a significant yet challenging task. In the present study, a Cu/CoOx catalyst was synthesized using a facile co-precipitation method, and subsequently used for the HDO of biomass derivatives. Under optimal reaction conditions, the conversion of 5-hydroxymethylfurfural reached 100% with a selectivity of ∼99% to 2,5-diformylfuran. In combination with the experimental results, systematic characterizations revealed that CoOx, as the acid site, tended to adsorb CO bonds, and the metal sites of Cu+ were inclined to adsorb CO bonds and enhance CO bond hydrogenation. Meanwhile, Cu0 was the main active site for 2-propanol dehydrogenation. The excellent catalytic performance could be attributed to the synergistic effects of Cu and CoOx. Further, by optimizing the ratio of Cu to CoOx, the Cu/CoOx catalysts exhibited notable performance in HDO of acetophenone, levulinic acid, and furfural, which verified the universality of the catalysts in the HDO of biomass derivatives.

Fluorescent Dye-Doped Brightening Polymer-Stabilized Bistable Cholesteric Liquid Crystal Films.

Brightening polymer-stabilized bistable cholesteric liquid crystal (PSBCLC) films with doped fluorescent dyes were prepared using the polymerization-induced phase separation (PIPS) method. The transmittance performance behavior of these films in both states (focal conic and planar) and absorbance change in multiple dye concentrations were studied using a UV/VIS/NIR spectrophotometer. The change occurring in dye dispersion morphology with different concentrations was obtained by means of the polarizing optical microscope. The maximum fluorescence intensity of different dye-doped PSBCLC films was measured using a fluorescence spectrophotometer. Moreover, the contrast ratios and driving voltages of these films were calculated and recorded to demonstrate film performance. Finally, the optimal concentration of dye-doped PSBCLC films with a high contrast ratio and a relatively low drive voltage was found. This is expected to have great potential applications in cholesteric liquid crystal reflective displays.

Data augmentation method based on the Gaussian kernel density for glioma diagnosis with Raman spectroscopy.

Glioma is an intracranial malignant brain tumor with high infiltration. It is difficult to identify the glioma boundary. Raman spectroscopy can potentially detect this boundary accurately in situ and in vivo during surgery. However, when building a classification model for an in vitro experiment, fresh normal tissue is difficult to obtain. The number of normal tissues is far less than that of glioma tissues, which leads to a classification bias toward the majority class. In this study, a data augmentation algorithm GKIM based on the Gaussian kernel density is proposed for the data augmentation of normal tissue spectra. A weight coefficient calculation formula is proposed based on the Gaussian density instead of a fixed coefficient to synthesize new spectra, which increases sample diversity and improves the robustness of modeling. Additionally, the fuzzy nearest neighbor distance replaces the general fixed neighbor number K to select the original spectra for synthesis. It automatically determines the nearest spectra and adaptively synthesizes new spectra according to the characteristics of the input spectra. It effectively overcomes the problem of the newly generated sample distribution being too concentrated in specific spaces for the common data augmentation method. In this study, 769 Raman spectra of glioma and 136 Raman spectra of normal brain tissue corresponding to 205 and 37 cases, respectively, were collected. The Raman spectra of the normal tissue were extended to 600. The accuracy, sensitivity, and specificity were 91.67%, 91.67%, and 91.67%. The proposed method achieved better predictive performance than traditional algorithms for class imbalance.

Evaluating the effect of vitreomacular interface abnormalities on anti-vascular endothelial growth factor treatment outcomes in diabetic macular edema by optical coherence tomography: A systematic review and meta-analysis.

PURPOSE: To evaluate the effect of vitreomacular interface (VMI) configuration on treatment outcomes after intravitreal anti-vascular endothelial growth factor (anti-VEGF) therapy for diabetic macular edema (DME) using optical coherence tomography (OCT). METHODS: A systematic literature search was performed on PubMed, Embase, web of science and clinicaltrials.gov. The primary outcome parameters were central macular thickness (CMT), best-corrected visual acuity (BCVA) and mean injection numbers. We performed this meta-analysis by Review Manager (RevMan) 5.4.1. RESULTS: The impact of epiretinal membrane (ERM), vitreomacular traction (VMT) and vitreomacular adhesion (VMA) on the treatment outcomes were analyzed separately. 9 clinical studies involving 699 eyes were eligible for the meta-analysis for evaluating the effect of ERM/VMT on efficacy. And 7 studies with 610 eyes were included to access whether VMA affected the response to anti-VEGF therapy in patients with DME. The ERM/VMT group had poorer CMT reductions than the control group at 1 month ([MD] 52.91 mm, P<0.00001), while no significant difference at 3 months ([MD] 43.95 mm, P = 0.22) and over 12 months ([MD] 30.51 mm, P = 0.45). No statistically significant difference in the mean BCVA change at 1 month ([MD] -0.03 Log MAR, P = 0.79), whereas ERM/VMT group had poor visual acuity gains at 3 months ([MD] 0.08 Log MAR, P = 0.003), and a tendency of poor vision improvement over 12 months follow-up ([MD] 0.07 Log MAR, P = 0.11). There was no significant difference in the visual and anatomical results over 3 months in DME patients with or without VMA ([MD] -21.92 mm, P = 0.09; [MD] 1.79 letters, P = 0.22). Besides, VMI configuration was not found to affect mean injection numbers. CONCLUSION: The limited evidence suggested that ERM/VMT was associated with worse CMT reduction at 1 month, poor BCVA gain at 3 months and a tendency of limited vision improvement over 12 months follow-up in DME patients treated with anti-VEGF agents. And VMA may not adversely affect the anatomic and functional outcomes. However, the results of this meta-analysis should be interpreted with caution because of the heterogeneity among study designs.

Study on the effects of different anti-VEGF drugs on fibrovascular membranes of proliferative diabetic retinopathy.

PURPOSE: To investigate the effects of different anti-VEGF drugs on fibrovascular membranes (FVM) in proliferative diabetic retinopathy (PDR). In addition, in vitro model was used to simulate the intraocular fibroblasts barrier to explore the penetration of different anti-VEGF drugs. METHODS: 24 eyes from 24 PDR patients with FVM were recruited for this prospective observational study. The patients were randomized to receive one of three anti-VEGF drugs (Ranibizumab, Conbercept, or Aflibercept). Then neovascular structures were assessed by optical coherence tomography angiography (OCTA) before intravitreal injection (pre-IVT) and 1, 2, and 3 days after intravitreal injection (post-IVT). The changes in vessels area (VSA), vessels percentage area (VPA), junction density (JD), and average lacunarity (AL) were analyzed by using the image processing software Angiotool. In vitro penetrating model with fibroblasts barrier was used to compare the effects of the three drugs on human retinal vascular endothelial cells (HRVECs) over 3 days by Cell proliferation measurement. Moreover, the drug concentrations in the penetrating model were detected by liquid chromatography-mass spectrometry (LC-MS). RESULTS: The VSA, VPA, and JD all decreased, while the AL increased in Ranibizumab group(n = 8), Conbercept group (n = 8), and Aflibercept group (n = 8) within 3 days (P<0.05). Meanwhile, under the condition of the same amount of substance, the inhibition effect of Ranibizumab on HRVEC was the strongest in the penetrating model evaluated by CCK8 absorbance experiments of HRVECs (FCCK8=6.493, PCCK8= 0.0051), and the number of transmembrane molecules in the Ranibizumab group was also the largest within 3 days (F = 8.209, P = 0.0006) among the three groups. CONCLUSION: Angiotool is feasible to reconstruct the neovascular structure on the FVM in OCTA images. The three different anti-VEGF drugs can significantly reduce the vascular area and density on the proliferating membranes, and there is no significant difference in the anti-neovascularization among the three drugs clinically. However, small molecule drug is more penetrating and move faster across membranes in vitro cell model. CLINICAL TRIAL REGISTRATION: This trial is registered with the Chinese Clinical Trial Registry (http://www.chictr.org.cn, registration number ChiCTR2300067476).