Conditional survival of patients with primary bone lymphoma of the spine: how survival changes after initial diagnosis.

Background: The current survival prediction methodologies for primary bone lymphoma (PBL) of the spine are deficient. This study represents the inaugural utilization of conditional survival (CS) to assess the outcome of this disease. Moreover, our objective was to devise a CS-based nomogram for predicting overall survival (OS) in real-time for spinal PBL. Methods: Patients with PBL of the spine diagnosed between January 2000 and December 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The OS was determined through the Kaplan-Meier method. The CS characteristic of patients with spinal PBL was delineated, with the CS being estimated utilizing the formula: CS(α|ß) = OS(α+ß)/OS(ß). CS(α|ß) denotes the probability of additional α-year survivorship, assuming the patient has already survived ß years after the time of observation. Three methods including univariate Cox regression, best subset regression (BSR) and the least absolute shrinkage and selection operator (LASSO) regression were used to identify predictors for CS-based nomogram construction. Results: Kaplan-Meier analysis was executed to determine the OS rate for these patients, revealing a survival rate of 68% and subsequently 63% at the 3-year and 5-year mark respectively. We then investigated the CS patterning exhibited by these patients and discovered the survival of PBL in the spine progressively improved with time. Meanwhile, through three different prognostic factor selection methods, we identified the best predicter subset including age, tumor histology, tumor stage, chemotherapy and marital status, for survival prediction model construction. Finally, we successfully established and validated a novel CS-based nomogram model for real-time and dynamic survival estimation. Moreover, we further designed a risk stratification system to facilitate the identification of high-risk patients. Conclusions: This is the first study to analyze the CS pattern of PBL of the spine. And we have also developed a CS-based nomogram that provide dynamic prognostic data in real-time, thereby aiding in the formulation of personalized treatment strategies in clinical practice.

Appropriate Drought Training Induces Optimal Drought Tolerance by Inducing Stepwise H2O2 Homeostasis in Soybean.

Soybean is considered one of the most drought-sensitive crops, and ROS homeostasis can regulate drought tolerance in these plants. Understanding the mechanism of H2O2 homeostasis and its regulatory effect on drought stress is important for improving drought tolerance in soybean. We used different concentrations of polyethylene glycol (PEG) solutions to simulate the progression from weak drought stress (0.2%, 0.5%, and 1% PEG) to strong drought stress (5% PEG). We investigated the responses of the soybean plant phenotype, ROS level, injury severity, antioxidant system, etc., to different weak drought stresses and subsequent strong drought stresses. The results show that drought-treated plants accumulated H2O2 for signaling and exhibited drought tolerance under the following stronger drought stress, among which the 0.5% PEG treatment had the greatest effect. Under the optimal treatment, there was qualitatively describable H2O2 homeostasis, characterized by a consistent increasing amplitude in H2O2 content compared with CK. The H2O2 signal formed under the optimum treatment induced the capacity of the antioxidant system to remove excess H2O2 to form a primary H2O2 homeostasis. The primary H2O2 homeostasis further induced senior H2O2 homeostasis under the following strong drought and maximized the improvement of drought tolerance. These findings might suggest that gradual drought training could result in stepwise H2O2 homeostasis to continuously improve drought tolerance.

Structural morphing in the viral portal vertex of bacteriophage lambda.

The portal protein of tailed bacteriophage plays essential roles in various aspects of capsid assembly, motor assembly, genome packaging, connector formation, and infection processes. After DNA packaging is complete, additional proteins are assembled onto the portal to form the connector complex, which is crucial as it bridges the mature head and tail. In this study, we report high-resolution cryo-electron microscopy (cryo-EM) structures of the portal vertex from bacteriophage lambda in both its prohead and mature virion states. Comparison of these structures shows that during head maturation, in addition to capsid expansion, the portal protein undergoes conformational changes to establish interactions with the connector proteins. Additionally, the independently assembled tail undergoes morphological alterations at its proximal end, facilitating its connection to the head-tail joining protein and resulting in the formation of a stable portal-connector-tail complex. The B-DNA molecule spirally glides through the tube, interacting with the nozzle blade region of the middle-ring connector protein. These insights elucidate a mechanism for portal maturation and DNA translocation within the phage lambda system. IMPORTANCE: The tailed bacteriophages possess a distinct portal vertex that consists of a ring of 12 portal proteins associated with a 5-fold capsid shell. This portal protein is crucial in multiple stages of virus assembly and infection. Our research focused on examining the structures of the portal vertex in both its preliminary prohead state and the fully mature virion state of bacteriophage lambda. By analyzing these structures, we were able to understand how the portal protein undergoes conformational changes during maturation, the mechanism by which it prevents DNA from escaping, and the process of DNA spirally gliding.

Risk factors for intraprocedural hypoxemia in patients with acute cerebral ischemia treated with vascular intervention and its impact on prognosis: A retrospective cohort study.

BACKGROUND: Acute cerebral infarction (ACI) is one of the most common ischemic cerebrovascular diseases in neurology, with high morbidity, mortality, and disability. Early thrombolytic treatment of ACI has significant efficacy, but intraprocedural complications of hypoxemia can significantly reduce the efficacy. This study aims to analyze the risk factors for intraprocedural hypoxemia in patients with ACI, so as to take effective measures in advance to reduce the likelihood of adverse patient outcomes. METHODS: We retrospectively analyzed a total of 238 patients with ACI treated with vascular interventions from May 2017 to May 2022. To assess and collate the patients' characteristics, factors associated with the development of intraprocedural hypoxemia. The independent risk factors for the development of intraprocedural hypoxemia were analyzed by binary logistic regression. RESULTS: A total of 238 patients were included in this study. Of these, intraprocedural hypoxemia occurred in 89 (37.4%). The results showed that old age (odds ratio [OR] = 2.666, P = 0.009), obesity (OR = 3.029, P = 0.003), smoking history (OR = 2.655, P = 0.010), preoperative oxygen saturation (SpO2) (OR = 0.001, P = 0.042), preoperative C-reactive protein (OR = 1.216, P = 0.002), and time from puncture to vascular recanalization (OR = 1.135, P = 0.000) were independent risk factors for intraprocedural hypoxemia in patients. The prognosis of the patients was assessed according to the modified Rankin scale, and the prognosis of the nonhypoxemia group was significantly better than that of the hypoxemia group. Regression analysis showed that intraprocedural hypoxemia (OR = 0.360, P = 0.001), postoperative lower extremity vein thrombosis (OR = 0.187, P = 0.018), hydrocephalus (OR = 0.069, P = 0.015), intracranial hemorrhage (OR = 0.116, P = 0.002), and reocclusion (OR = 0.217, P = 0.036) were independent risk factors for poor prognosis. CONCLUSIONS: Currently, intravascular hypoxemia in patients with ACI has a serious impact on prognosis. Clinical work should attach great importance to the clinical characteristics of patients, identify relevant risk factors, and aggressively take personalized therapeutic actions to improve patients' prognosis.

Conditional survival analysis and dynamic survival prediction for intracranial solitary-fibrous tumor/hemangiopericytoma.

BACKGROUND: As the form of World Health Organization Central Nervous System (WHO CNS) tumor classifications is updated, there is a lack of research on outcomes for intracranial combined solitary-fibrous tumor and hemangiopericytoma (SFT/HPC). This study aimed to explore conditional survival (CS) pattern and develop a survival prediction tool for intracranial SFT/HPC patients. METHODS: Data of intracranial SFT/HPC patients was gathered from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. The patients were split into training and validation groups at a 7:3 ratio for our analysis. CS is defined as the likelihood of surviving for a specified period of time (y years), given that the patient has survived x years after initial diagnosis. Then, we used this definition of CS to analyze the intracranial SFT/HPC patients. The least absolute shrinkage and selection operator (LASSO) regression and best subset regression (BSR) were employed to identify predictive factors. The Multivariate Cox regression analysis was applied to establish a novel CS-based nomogram, and a risk stratification system was developed using this model. RESULTS: From the SEER database, 401 patients who were diagnosed with intracranial SFT/HPC between 2000 and 2019 were identified. Among them, 280 were included in the training group and 121 were included in the internal validation group for analysis. Our study revealed that in intracranial SFT/HPC, 5-year survival rates saw significant improvement ranging from 78% at initial diagnosis to rates of 83%, 87%, 90%, and 95% with each successive year after surviving for 1-4 years. The LASSO regression and BSR identified patient age, tumor behavior, surgery and radiotherapy as predictors of CS-based nomogram development. A risk stratification system was also successfully constructed to facilitate the identification of high-risk patients. CONCLUSION: The CS pattern of intracranial SFT/HPC patients was outlined, revealing a notable improvement in 5-year survival rates after an added period of survival. Our newly-established CS-based nomogram and risk stratification system can provide a real-time dynamic survival estimation and facilitate the identification of high-risk patients, allowing clinicians to better guide treatment decision for these patients.

Comprehensive analysis of risk factors and pathogenetic characteristics associated with surgical site infections following craniotomy procedures.

Craniotomies are intricate neurosurgical procedures susceptible to post-operative complications, among which surgical site infections (SSIs) are particularly concerning. This study sought to elucidate the potential risk factors and pathogenetic characteristics associated with SSIs following craniotomy procedures in a clinical setting. A retrospective study was conducted from May 2020 to May 2023, examining patients subjected to elective or emergency craniotomies. The cohort underwent post-operative surveillance for SSIs, facilitating patient classification into SSI and Non-SSI groups based on infection occurrence. Data collection encapsulated demographic and clinical parameters, including American Society of Anesthesiologists (ASA) classifications, and operative factors. SSIs were diagnosed via an integrated approach combining clinical symptoms, microbiological culture findings and pertinent laboratory tests. A rigorous statistical methodology employing IBM's SPSS version 27.0 was utilised for data analysis. In a univariate analysis, significant risk factors for post-craniotomy SSIs were identified, with patients aged over 60 displaying a pronounced susceptibility. Moreover, surgeries exceeding a duration of 4 h heightened infection risks. Elevated ASA grades denoted an increased prevalence of SSIs, as did emergency procedures and higher National Nosocomial Infections Surveillance scores. Multivariate analysis pinpointed epidural/subdural drainage as a protective measure against SSIs, whereas emergency surgeries, operative times beyond 4 h and subsequent surgeries within the hospital stay amplified infection risks. Notably, coagulase-negative Staphylococcus dominated the identified pathogens at 28.09%, followed by Escherichia coli (17.98%), Klebsiella pneumoniae (10.11%) and Staphylococcus aureus (11.24%), underscoring the need for diverse prophylactic measures. SSIs following craniotomies present a multifaceted challenge influenced by a confluence of patient-related, operative and post-operative determinants. Understanding these risk factors is paramount in refining surgical protocols and post-operative care strategies to mitigate SSI incidence.

Architecture of the bacteriophage lambda tail.

Bacteriophage lambda has a double-stranded DNA genome and a long, flexible, non-contractile tail encoded by a contiguous block of 11 genes downstream of the head genes. The tail allows host recognition and delivery of viral DNA from the head shell to the cytoplasm of the infected cell. Here, we present a high-resolution structure of the tail complex of bacteriophage lambda determined by cryoelectron microscopy. Most component proteins of the lambda tail were determined at the atomic scale. The structure sheds light on the molecular organization of the extensively studied tail of bacteriophage lambda.

Decision Tree Model for Predicting the Overall Survival of Patients with Diffused Large B-Cell Lymphoma in the Central Nervous System.

OBJECTIVE: To identify the significant predictors of overall survival for patients living with diffused large B-cell lymphoma (DLBCL) in the central nervous system and establish a novel decision tree model to help predict survival status at several time points. METHODS: Patients diagnosed with DLBCL were identified from the SEER database and randomly divided into training and test samples (6:4). Dichotomous decision trees were developed for survival status at 3, 12, 24, and 60 months. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy rate, and area under the receiver operating characteristic curve were calculated to evaluate the model performance. RESULTS: A total of 2998 patients were included, with 1799 and 1199 patients divided into the training and testing groups. Decision trees for 3, 12, 24, and 60 months survival status were generated. Chemotherapy and patient's age were of the primary importance for prognosis in the novel models. Favorable consistency between the predicted and actual survival status was presented. The accuracy rates were 0.79, 0.71, 0.68, and 0.86 for training sample at 3, 12, 24, and 60 months, respectively, and 0.75, 0.69, 0.58, and 0.84 for test sample at 3, 12, 24, and 60 months, respectively. The area under the receiver operating characteristic curve values ranged between 0.645 and 0.721 for the training sample and between 0.607 and 0.712 for the test sample. CONCLUSIONS: Novel decision tree models were established for predicting the 3, 12, 24, and 60 months survival status of patients with DLBCL. The newly developed models were verified using training and test samples, showing favorable accuracy and predictive value on overall survival.

Resonance prediction and inverse design of multi-core selective couplers based on neural networks.

Resonance analysis and structural optimization of multi-channel selective fiber couplers currently rely on numerical simulation and manual trial and error, which is very repetitive and time consuming. To realize fast and accurate resonance analysis and calculation, we start with dual-core structures and establish forward classification and regression neural networks to classify and predict different resonance properties, including resonance types, operating wavelength, coupling coefficient, coupling length, 3 dB bandwidth, and conversion efficiency. The pre-trained forward neural networks for dual-core fibers can also realize accurate and fast prediction for multi-core fibers if the mode energy exchange occurs only between one surrounding core and the central core. For the inverse design, a tandem neural network has been constructed by cascading the pre-trained forward neural network and the inverse network to solve the non-uniqueness problem and provide an approach to search for appropriate and desired multi-core structures. The proposed forward and inverse neural networks are efficient and accurate, which provides great convenience for resonance analysis and structural optimization of multi-channel fiber structures and devices.

Downregulation of USP34 Inhibits the Growth and Migration of Pancreatic Cancer Cells via Inhibiting the PRR11.

BACKGROUND: Pancreatic cancer (PC) is a highly lethal malignancy worldwide. Our previous study indicated that overexpression of USP34 could promote tumor growth in PC cells. Therefore, this study aimed to further investigate the role of USP34 during the tumorigenesis of PC. METHODS: The level of USP34 in PANC-1 and MiaPaCa-2 cells transfected with USP34-shRNAs was detected by RT-qPCR. Moreover, transwell migration and Annexin V/PI analysis were conducted to detect cell migration and apoptosis, respectively. RESULTS: In this study, downregulation of USP34 markedly inhibited proliferation and migration, and induced apoptosis in PANC-1 cells. Moreover, silencing of USP34 obviously downregulated the levels of PRR11 and p-p38 in PANC-1 cells. An in vivo study in nude mice bearing PANC-1 cell xenografts confirmed these results. CONCLUSION: Downregulation of USP34 could inhibit proliferation and migration in PANC-1 cells via inhibiting PRR11, and inactivating p38 MAPK signaling. Therefore, USP34 might be a potential therapeutic target for the treatment of PC.

Active disturbance rejection control of 5-degree-of-freedom bearingless permanent magnet synchronous motor based on fuzzy neural network inverse system.

To realize the high performance operation of the 5-degree-of-freedom bearingless permanent magnet synchronous motor (5-DOF-BPMSM), a novel decoupling control strategy combining fuzzy neural network inverse system (FNNIS) with active disturbance rejection control (ADRC) is proposed. Firstly, fuzzy neural network (FNN) is employed to approach the inverse system of the 5-DOF-BPMSM. By connecting the obtained inverse system with the original system, six independent pseudo-linear subsystems are constructed. Then, considering the influence of parametric variations and external disturbances in the process of operation, the ADRC theory is employed to design additional closed-loop controllers to ensure the stability of the pseudo-linear subsystems. Finally, comparative simulation and experimental results indicate that the proposed control strategy can achieve better control performance.

USP34 Regulated Human Pancreatic Cancer Cell Survival via AKT and PKC Pathways.

Pancreatic cancer is known to be a fatal disease, which is difficult to be diagnosed in its early stages. Ubiquitin-Specific Protease 34 (USP34) are closely related to human cancers in the development and progression. However, there are rarely studies about the role of USP34 in pancreatic cancer. Thus, we aimed to investigate the effect of USP34 in human pancreatic cancer. Short-hairpin RNA targeting USP34 (USP34-shRNA) and USP34 overexpression lentivirus were used in the current study. The level of USP34 in human pancreatic cancer (PANC-1) cells were then analyzed by quantitative (q)RT-PCR. In addition, Western blotting was used to examine phosphorylated (p)-AKT, p-protein kinase C (PKC) and p-extracellular signal-regulated kinase (ERK) protein levels. CCK-8 assay, flow cytometry, and migration assay were used to detect cell proliferation, apoptosis and migration, respectively in vitro. According to the result of qRT-PCR and Western blotting, USP34-shRNA1 significantly downregulated USP34 gene level in PANC-1 cell. Subsequently, Western blotting assay indicated that USP34 silencing significantly down-regulated the expression of p-AKT and p-PKC in cells. On the other hand, USP34 overexpressing remarkably up-regulated the expression of p-AKT and p-PKC in cells. In addition, USP34 overexpression promoted PANC-1 cell proliferation and migration via up-regulating the proteins of p-AKT and p-PKC. Moreover, USP34 overexpression reversed AKT inhibitor and PKC inhibitor induced PACN-1 cell apoptosis. Our results indicated USP34 regulated h PANC-1 cell survival via AKT and PKC pathways, and which played a pro-survival role in human pancreatic cancer. Therefore, we suggested USP34 could be a potential therapeutic target for pancreatic cancer.

Temperature Management With Paracetamol in Acute Stroke Patients: Evidence From Randomized Controlled Trials.

Whether or not paracetamol can improve functional outcomes in patients with acute stroke has been examined in several clinical trials. The inconsistent results of these trials have caused great controversy regarding the need for further studies. In the present meta-analysis, we have aimed to address this controversy. The main databases (Medline, Embase, and Cochrane Library) were searched for randomized controlled trials involving the use of paracetamol in acute stroke patients. Pooled relative risks (RRs) or mean differences (MDs) and 95% confidence intervals (CIs) were calculated using a random-effects model. A total of 1,836 patients were pooled from four phase II and two phase III trials. The use of paracetamol resulted in a significant reduction in body temperature after 24 h (MD, -0.21; 95% CI, -0.28 to -0.13; P < 0.001) and mortality rate after 7-14 days (RR, 0.62; 95% CI, 0.41-0.93; P = 0.02) when compared with the placebo group; however, no effect of paracetamol was observed in the modified Rankin Scale score (RR, 1.07; 95% CI, 0.91-1.27; P = 0.40) or Barthel Index score (RR, 0.98; 95% CI, 0.91-1.06; P = 0.63) at 30 or 90 days. No significant differences were observed with respect to serious adverse events between the paracetamol and the placebo groups (P > 0.05). Subgroup analyses were performed to detect the source of the heterogeneity, which showed that ischemic stroke, serious condition at baseline, and late time-to-treatment had adverse impacts on the effect of paracetamol post stroke. In conclusion, temperature management with paracetamol in acute stroke patients is safe. Although paracetamol reduced the mortality rate in the early stage of stroke, it did not appear to affect long-term mortality and functional recovery. It should be noted that this conclusion is based on the results from studies of poor quality. A large clinical trial with a focus on early treatment of patients with acute stroke is warranted.

Development and validation of the hypertensive intracerebral hemorrhage prognosis models.

To develop and validate the prognosis model of hypertensive intracerebral hemorrhage based on admission characteristics, which would be applied to predict the 3-month outcome.For developing the prognosis models, we studied data from 325 patients with retrospectively consecutive hypertensive intracerebral hemorrhage admitted between 2012 and 2016. The predictive value of admission characteristics was tested in logistic regression models, presenting 3-month outcome as the primary outcome. The performance of the models was tested by discrimination and calibration. After development, internal and external validations were used to test the function.The multivariate analysis of logistic regression indicated that age, Glasgow coma scale score, pupillary light reflex, hypoxemia, intracerebral hemorrhage volume, blood glucose, and D-dimer level were independent factors of the hypertensive intracerebral hemorrhage prognosis model. The prognosis model based on those admission risk factors worked well. The receiver operating characteristic curve was used to analyze the discriminant ability of model A, model A + B, and model A + B + C. Specifically, the area under the receiver operating characteristic curve increased from 0.816 (model A; 95% CI, 0.760-0.872) to 0.913 (model A + B + C; 95% CI, 0.881-0.946), and the models were not overoptimistic and were applicably confirmed by internal and external validations respectively.This prognosis model could be used to predict the prognosis of patients with hypertensive intracerebral hemorrhage early, simply and accurately, contributing to the clinical treatment eventually.

Discovery of AG-120 (Ivosidenib): A First-in-Class Mutant IDH1 Inhibitor for the Treatment of IDH1 Mutant Cancers.

Somatic point mutations at a key arginine residue (R132) within the active site of the metabolic enzyme isocitrate dehydrogenase 1 (IDH1) confer a novel gain of function in cancer cells, resulting in the production of d-2-hydroxyglutarate (2-HG), an oncometabolite. Elevated 2-HG levels are implicated in epigenetic alterations and impaired cellular differentiation. IDH1 mutations have been described in an array of hematologic malignancies and solid tumors. Here, we report the discovery of AG-120 (ivosidenib), an inhibitor of the IDH1 mutant enzyme that exhibits profound 2-HG lowering in tumor models and the ability to effect differentiation of primary patient AML samples ex vivo. Preliminary data from phase 1 clinical trials enrolling patients with cancers harboring an IDH1 mutation indicate that AG-120 has an acceptable safety profile and clinical activity.

Enhancement of Eu3+ Red Upconversion in Lu2O3: Yb3+/Eu3+ Powders under the Assistance of Bridging Function Originated from Ho3+ Tridoping.

The red upconversion (UC) emission of Eu3+ ions in Lu2O3: Yb3+/Eu3+ powders was successfully enhanced by tridoping Ho3+ ions in the matrix, which is due to the bridging function of Ho3+ ions. The experiment data manifest that, in Yb3+/Eu3+/Ho3+ tridoped system, the Ho3+ ions are first populated to the green emitting level 5F4/5S2 through the energy transfer (ET) processes from the excited Yb3+ ions. Subsequently, the Ho3+ ions at 5F4/5S2 level can transfer their energy to the Eu3+ ions at the ground state, resulting in the population of Eu3+5D0 level. With the assistance of the bridging function of Ho3+ ion, this ET process is more efficient than the cooperative sensitization process between Yb3+ ion and Eu3+ ion. Compared with Lu2O3: 5 mol % Yb3+/1 mol % Eu3+, the UC intensity of Eu3+5D0→7F2 transition in Lu2O3: 5 mol % Yb3+/1 mol % Eu3+/0.5 mol % Ho3+ is increased by a factor of 8.

AG-348 enhances pyruvate kinase activity in red blood cells from patients with pyruvate kinase deficiency.

Pyruvate kinase (PK) deficiency is a rare genetic disease that causes chronic hemolytic anemia. There are currently no targeted therapies for PK deficiency. Here, we describe the identification and characterization of AG-348, an allosteric activator of PK that is currently in clinical trials for the treatment of PK deficiency. We demonstrate that AG-348 can increase the activity of wild-type and mutant PK enzymes in biochemical assays and in patient red blood cells treated ex vivo. These data illustrate the potential for AG-348 to restore the glycolytic pathway activity in patients with PK deficiency and ultimately lead to clinical benefit.

Improvement of Green Upconversion Monochromaticity by Doping Eu3+ in Lu2O3:Yb3+/Ho3+ Powders with Detailed Investigation of the Energy Transfer Mechanism.

The monochromaticity improvement of green upconversion (UC) in Lu2O3:Yb3+/Ho3+ powders has been successfully realized by tridoping Eu3+. The integral area ratio of green emission to red emission of Ho3+ increases 4.3 times with increasing Eu3+ doping concentration from 0 to 20 mol %. The energy transfer (ET) mechanism in the Yb3+/Ho3+/Eu3+ tridoping system has been investigated carefully by visible and near-infrared (NIR) emission spectra along with the decay curves, revealing the existence of ET from the Ho3+5F4/5S2 level tothe Eu3+5D0 level and ET from the Ho3+5I6 level to the Eu3+7F6 level. In addition, the population routes of the red-emitting Ho3+5F5 level in the Yb3+/Ho3+ codoped system under 980 nm wavelength excitation have also been explored. The ET process from the Yb3+2F5/2 level to the Ho3+5I7 level and the cross-relaxation process between two nearby Ho3+ ions in the 5F4/5S2 level and 5I7 level, respectively, have been demonstrated to be the dominant approaches for populating the Ho3+5F5 level. The multiphonon relaxation process originating from the Ho3+5F4/5S2 level is useless to populate the Ho3+5F5 level. As the energy level gap between the Ho3+5I7 level and Ho3+5I8 level matches well with that between Eu3+7F6 level and Eu3+7F0 level, the energy of the Ho3+5I7 level can be easily transferred to the Eu3+7F6 level by an approximate resonant ET process, resulting in a serious decrease in the red UC emission intensity. Since this ET process is more efficient than the ET from the Ho3+5F4/5S2 level to the Eu3+5D0 level as well as the ET from the Ho3+5I6 level to the Eu3+7F6 level, the integral area ratio of green emission to red emission of Ho3+ has been improved significantly.

Correlative linear neighborhood propagation for video annotation.

Recently, graph-based semisupervised learning methods have been widely applied in multimedia research area. However, for the application of video semantic annotation in multilabel setting, these methods neglect an important characteristic of video data: The semantic concepts appear correlatively and interact naturally with each other rather than exist in isolation. In this paper, we adapt this semantic correlation into graph-based semisupervised learning and propose a novel method named correlative linear neighborhood propagation to improve annotation performance. Experiments conducted on the Text REtrieval Conference VIDeo retrieval evaluation data set have demonstrated its effectiveness and efficiency.