A novel lipid metabolism-based risk model associated with immunosuppressive mechanisms in diffuse large B-cell lymphoma.

BACKGROUND: The molecular diversity exhibited by diffuse large B-cell lymphoma (DLBCL) is a significant obstacle facing current precision therapies. However, scoring using the International Prognostic Index (IPI) is inadequate when fully predicting the development of DLBCL. Reprogramming lipid metabolism is crucial for DLBCL carcinogenesis and expansion, while a predictive approach derived from lipid metabolism-associated genes (LMAGs) has not yet been recognized for DLBCL. METHODS: Gene expression profiles of DLBCL were generated using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The LASSO Cox regression was used to construct an effective predictive risk-scoring model for DLBCL patients. The Kaplan-Meier survival assessment was employed to compare a given risk score with the IPI score and its impact on the survival of DLBCL patients. Functional enrichment examination was performed utilizing the KEGG pathway. After identifying hub genes via single-sample GSEA (ssGSEA), immunohistochemical staining and immunofluorescence were performed on lymph node samples from control and DLBCL patients to confirm these identified genes. RESULTS: Sixteen lipid metabolism- and survival-associated genes were identified to construct a prognostic risk-scoring approach. This model demonstrated robust performance over various datasets and emerged as an autonomous risk factor for predicting the development of DLBCL patients. The risk score could significantly distinguish the development of DLBCL patients from the low-risk and elevated-risk IPI classes. Results from the inhibitory immune-related pathways and lower immune scores suggested an immunosuppressive phenotype within the elevated-risk group. Three hub genes, MECR, ARSK, and RAN, were identified to be negatively correlated with activated CD8 T cells and natural killer T cells in the elevated-risk score class. Ultimately, it was determined that these three genes were expressed by lymphoma cells but not by T cells in clinical samples from DLBCL patients. CONCLUSION: The risk level model derived from 16 lipid metabolism-associated genes represents a prognostic biomarker for DLBCL that is novel, robust, and may have an immunosuppressive role. It can compensate for the limitations of the IPI score in predicting overall survival and has potential clinical application value.

IL-6 promotes chemoresistance via upregulating CD36 mediated fatty acids uptake in acute myeloid leukemia.

Chemoresistance contributes to poor survival and high relapse risk in acute myeloid leukemia (AML). As a pro-inflammatory cytokine, interleukin-6 (IL-6) plays a vital role in the chemoresistance of malignancies. However, the underlying mechanisms of chemoresistance in AML have not been widely studied. Lipid metabolism, which contributes to chemoresistance in AML, is enhanced by IL-6 in skeletal muscle cells. We hypothesized that IL-6 promotes the chemoresistance of AML by promoting lipid metabolism. Based on the positive correlation between IL-6 receptor expression and the cellular response to exogenous IL-6, we performed Gene Ontology analysis of a dataset consisting the information of 151 AML patients from The Cancer Genome Atlas. We found that lipid transport-associated genes were upregulated in the high IL-6 receptor expression group. Additionally, IL-6 promoted fatty acid (FA) uptake in both AML cell lines and primary AML cells. Inhibition of FA uptake by sulfo-N-succinimidyl oleate repressed IL-6-induced chemoresistance. Western blotting, quantitative polymerase chain reaction, and chromatin immunoprecipitation assays indicated that IL-6 promoted CD36 expression at both the mRNA and protein levels through stat3 signaling. Knockout of CD36 or stat3 repressed IL-6-induced FA uptake and chemoresistance. Furthermore, in five human AML samples, we validated that compared to CD36-cells, CD36+ primary AML cells were less sensitive to cytosine arabinoside (Ara-c) and that blockade of CD36 re-sensitized CD36+ AML cells to Ara-c. Mice injected with CD36 knockout cells followed by treatment with Ara-c showed markedly decreased leukemia burden and prolonged survival in vivo. Finally, treatment with the CD36 antibody in combination with Ara-c exhibited synergistic effects in vivo. In conclusion, IL-6 promotes chemoresistance in AML through the stat3/CD36-mediated FA uptake. Blockade of CD36 improved the effect of Ara-c, representing a promising strategy for AML therapy.

Ultrasensitive fluorescent detection of telomerase activity based on tetrahedral DNA nanostructures as carriers for DNA-templated silver nanoclusters.

Precise evaluation of telomerase activity is essential for the clinical diagnosis of early tumors. Herein, we have ingeniously designed a tetrahedral DNA nanostructure, with hairpin-shaped DNA probes rich in cytosine bases at four vertices for telomerase detection. The DNA-templated silver nanoclusters can be formed after the addition of Ag. Then the introduction of telomerase adds the single-strand TTAGGG extension, which can "turn on" the fluorescence of silver nanoclusters quickly by the proximity of the resulting guanine-rich sequences to silver nanoclusters and realize accurate detection of telomerase activity. In this study, integration of high stability tetrahedral DNA nanostructure and fluorescence signal amplification of four DNA-templated silver nanoclusters offers the advantage of high sensitivity, with a low detection limit of 1 cell. More than that, this method is low-cost, facile, and feasible for practical clinical applications.

Proton Transfer in Nitromethane-Ammonia Clusters under VUV Single-Photon Ionization Explored by Infrared Spectroscopy and Theoretical Calculations.

It is known that the acidity and reactivity of the CH bond can be enhanced after ionization. Also, this property plays a pivotal role in proton transfer reaction and in the formation of new molecules. Herein, infrared spectroscopy and high-precision quantum chemical calculations are used to study the neutral and cationic clusters of nitromethane-ammonia (CH3NO2-NH3). It is found that in the neutral cluster, CH3NO2 and NH3 are mainly bonded by three intermolecular hydrogen bonds, in which electrostatic contribution plays a major role. After vacuum ultraviolet (VUV) single-photon ionization of CH3NO2-NH3, the positive charge redistributes from the ionized nitrogen atom of NH3 to the CH3NO2 molecule immediately. Then, the proton of CH3NO2 transfers to NH3 to form a proton-transferred type structure CH2NO2-NH4+, without any effective energy barrier, due to the positive hyperconjugation of cationic nitromethane. A closed loop of positive charge transfer takes place in the CH3NO2-NH3 cluster after VUV ionization. The present work demonstrates that both the proton transfer reaction and charge transfer process have occurred in the ionized CH3NO2-NH3 cluster. Moreover, it is found that the proton transfer reaction is a result of the highly acidic CH bond caused by hyperconjugation between the σ (CH) bond and π orbital.

Bio-inspired construction of a semi-artificial enzyme complex for detecting histone acetyltransferases activity.

Herein, an electrochemical method to detect histone acetyltransferases activity (HAT) has been developed based on the reduction of G-Quadruplex-Cu(ii) metalloenzyme activity. A G-quadruplex-Cu(ii) metalloenzyme has excellent peroxidase property, generating strong electrochemical signal. In the presence of HAT, it can catalyze substrate peptide acetylation and produce large amounts of Coenzyme A (CoA). The electrochemical signal of G-Quadruplex-Cu(ii) is weak due to the competitive combination between G-Quadruplex and CoA with Cu(ii), resulting in the direct quantitative detection of HAT. The detection limit for HAT is about 0.14 nM using this strategy and the cost is quite low since the developed assay method is label-free and antibody-free due to the use of low-cost DNA and Cu2+. Since this assay method can be employed to detect HAT in serum, it may be useful in disease diagnosis in the future.

Conformational Landscapes and Infrared Spectra of Gas-phase Interstellar Molecular Clusters [(C3H3N)(CH3OH)n, n = 1-4].

Acrylonitrile (A) is one of the important interstellar molecules, which is considered closely related to the origin of life. And methanol (M) is one of the commonly used solvents, which is also found in outer space. Herein, we obtained the infrared (IR) spectra of size-selected AMn (n = 1-4) clusters in supersonic jet by monitoring their fragments of H+AMn-1 (n = 1-4) with vacuum ultraviolet single-photon soft ionization/IR-depletion technique. IR spectra of AMn (n = 1-4) clusters were recorded in the CH and OH vibration bands in the range of 2700-3800 cm-1. Spectra of AMn (n = 1-4) clusters are similar in the CH stretching regions, while those show significant variations in the OH stretching regions with the increase of methanol molecules. Calculated IR spectra, which were predicted with the B3LYP-D3(BJ)/aug-cc-pVDZ method, were employed to compare with the experimental results. For AM, AM2, and AM3, the structures with the methanol cyclic hydrogen bonded with [N1-C4(H6)] of acrylonitrile are more stable than the other H-bonded structures. For the most stable structures of AM4, however, the results show that the acrylonitrile is binding to a H-bonded ring formed by OH groups of four methanol molecules. The AM, AM2, and AM3 conformers with the single ring on the C1 side of acrylonitrile, such as C1-AM-a, C1-AM2-a, and C1-AM3-a, are dominant in the gas phase, while the C2-AM4-a conformer with the H-bonded ring formed by the OH groups on the C2 side of acrylonitrile is more stable than that of CM4-A-a in our experimental conditions (>130 K). These findings may provide valuable insight into the microsolvation process of the interstellar molecules and other biomolecules in gas phase.

Highly sensitive detection of Smoothened based on the drug binding and rolling cycle amplification.

Metastases are the leading causes of death in cancer patients. Due to intimate connection with metastasis, Smoothened (Smo) has become a therapeutic target for antimetastatic drugs and can provide early warning of metastasis in breast cancer. Thus, we have developed an electrochemical method in Smo analysis based on small-molecule drugs. Smo on the metastatic cell surface can be internalized after combination with the small-molecule drug. The surplus small-molecule drug and rolling circle amplification (RCA) primer are competitively binding with capture probe on the electrode surface through the click chemical reaction. After RCA reaction, methylene blue is used to label the RCA product. In this process, the more Smo on the metastatic cell surface, the more RCA primer is bound with peptide on the electrode. Therefore, the obtained signal response is positively correlated to Smo on the cancer cells. Moreover, the RCA provides sufficiently high sensitivity, enabling the limit of detection of Smo to be calculated as 0.1 pM (S/N = 3). Owing to its desirable sensitivity, excellent reproducibility, and high selectivity, the proposed method may hold great potential in clinical practice in the future. Graphical abstract.

Click DNA cycling in combination with gold nanoparticles loaded with quadruplex DNA motifs enable sensitive electrochemical quantitation of the tuberculosis-associated biomarker CFP-10 in sputum.

An electrochemical aptamer-based assay is described for the determination of CFP-10 which is an early secretary biomarker of Mycobacterium tuberculosis. CFP-10 is specifically captured by its aptamer and then induces a DNA cross-linking click reaction, the release of CFP-10, and an amplification cycle of repeated CFP-10 release. This mechanism (with dual amplification via DNA click and target release cycle) causes more and more CFP-10 Apt strands on the electrode surface to expose their 5' overhang and to hybridize with the DNA complexes linked to the gold nanoparticles (AuNPs). Consequently, large amounts of AuNPs, each loaded with a number of quadruplex DNA motifs, can be bound on the electrode surface and remarkably enhance the signal. Under optimal conditions, the method has a detection limit as low as 10 pg.mL-1 of CFP-10. The method was successfully applied to the diagnosis of M. tuberculosis in sputum. Graphical abstract Schematic representation of an electrochemical CFP-10 (10-kDa culture filtrate protein) assay using click DNA cycling in combination with gold nanoparticles loaded with quadruplex DNA motifs. Click chemistry reaction between Dibenzocyclooctyne (DBCO)-DNA and azido-DNA can liberate the CFP-10 antigen for the next cycle, which can be viewed as the first amplification step. G-quadruplex-based DNAzyme is formed due to the guanine-rich sequences of DNA S1, which can be viewed as the second amplification step.

A fluorometric method for determination of the activity of T4 polynucleotide kinase by using a DNA-templated silver nanocluster probe.

The authors describe a turn-off fluorometric method for the determination of the activity of the T4 polynucleotide kinase (T4 PNK). It is based on the use of DNA-templated silver nanoclusters (AgNCs). DNA probes with terminal 5' hydroxy groups are used as substrates for DNA phosphatases. If subsequently treated with T4 PNK and Lambda exonuclease (λ exo), the AgNC DNA probes with a modified C-rich sequence and the G-rich sequence is separated. Upon their separation, the strong fluorescence (with excitation/emission maxima at 580/650 nm) that is caused by the proximity of the G-rich region and the C-rich region in the AgNCs decreases sharply. This enabled the fluorometric kinetic determination of the activity of T4 PNK. The assay is characterized by a wide linear range (from 0.01 to 12.5 U·mL-1), a low detection limit (0.01 U·mL-1) and short assay time (typically 60 min). This makes it a promising tool for use in studying processes related to DNA phosphorylation, in drug discovery and in diagnostics. Graphical abstract A turn-off fluorometric method for the determination of the activity of the T4 polynucleotide kinase (T4 PNK) has been developed. It is based on the use of DNA-templated silver nanoclusters (AgNCs). This makes it a promising tool for use in studying processes related to DNA phosphorylation, in drug discovery and in diagnostics.

Blind Poissonian reconstruction algorithm via curvelet regularization for an FTIR spectrometer.

An FTIR spectrometer often suffers from common problems of band overlap and Poisson noises. In this paper, we show that the issue of infrared (IR) spectrum degradation can be considered as a maximum a posterior (MAP) problem and solved by minimized a cost function that includes a likelihood term and two prior terms. In the MAP framework, the likelihood probability density function (PDF) is constructed based on the observed Poisson noise model. A fitted distribution of curvelet transform coefficient is used as spectral prior PDF, and the instrument response function (IRF) prior is described based on a Gauss-Markov function. Moreover, the split Bregman iteration method is employed to solve the resulting minimization problem, which highly reduces the computational load. As a result, the Poisson noises are perfectly removed, while the spectral structure information is well preserved. The novelty of the proposed method lies in its ability to estimate the IRF and latent spectrum in a joint framework, thus eliminating the degradation effects to a large extent. The reconstructed IR spectrum is more convenient for extracting the spectral feature and interpreting the unknown chemical or biological materials.

Nonlocal low-rank-based blind deconvolution of Raman spectroscopy for automatic target recognition.

Raman spectroscopy often suffers from the problems of band overlap and random noise. In this work, we develop a nonlocal low-rank regularization (NLR) approach toward exploiting structured sparsity and explore its applications in Raman spectral deconvolution. Motivated by the observation that the rank of a ground-truth spectrum matrix is lower than that of the observed spectrum, a Raman spectral deconvolution model is formulated in our method to regularize the rank of the observed spectrum by total variation regularization. Then, an effective optimization algorithm is described to solve this model, which alternates between the instrument broadening function and latent spectrum until convergence. In addition to conceptual simplicity, the proposed method has achieved highly competent objective performance compared to several state-of-the-art methods in Raman spectrum deconvolution tasks. The restored Raman spectra are more suitable for extracting spectral features and recognizing the unknown materials or targets.

Infrared spectrum blind deconvolution algorithm via learned dictionaries and sparse representation.

Band overlap and random noise are a serious problem in infrared spectra, especially for aging spectrometers. In this paper, we have presented a simple method for spectrum restoration. The proposed method is based on local operations, and involves sparse decompositions of each spectrum piece under an evolving overcomplete dictionary, and a simple averaging calculation. The content of the dictionary is of prime importance for the deconvolution process. Quantitative assessments of this technique on simulated and real spectra show significant improvements over the state-of-the-art methods. The proposed method can almost eliminate the effects of instrument aging. The features of these deconvoluted infrared spectra are more easily extracted, aiding the interpretation of unknown chemical mixtures.

The anti-cancerous activity of recombinant trichosanthin on prostate cancer cell PC3.

CONTEXT: Trichosanthin produced in the root tube of Trichosanthes kirilowii shows anti-tumor activity on a series of cancer cells including Hela, MCF-7, HL-60. But there is little information about its effect on the carcinogenesis of prostate cancer. OBJECTIVE: This work was designed to study the role of trichosanthin on prostate cancer cells PC3. MATERIALS AND METHODS: Trichosanthin was expressed in BL21 strain and purified by affinity chromatography. MTT assay was designed to determine the effect of trichosanthin on growth of PC3 cells at doses of 10, 20, 40, 60, 80, and 120 µg/ml. Then the effect of 50 µg/ml rTCS alone or combined with 2 µM IL-2 on PC3 cell proliferation was analyzed. And the mechanism of rTCS was studied by western blot. After that the in vivo effect of rTCS combined with IL-2 was explored in mice bearing PC3 xenograft tumor. RESULTS: Trichosanthin was successfully expressed in BL21 and purified by 100 mM imidazole. It was shown to inhibit proliferation of PC3 cells in a dose-dependent manner with IC50 50.6 µg/ml. When combined with cytokine IL-2, a significant synergic effect was obtained. The inhibition rate on PC3 was around 50 % in combination group while only 35.5 % in single rTCS group at 50 µg/ml. Further, the expression of full length caspase-8 and Bcl-2 decreased significantly while cleaved caspase-8 and Bax were up-regulated, which suggest that caspase-8-mediated apoptosis pathway may be activated by rTCS in PC3 cells. Moreover, our data demonstrated that tumor volume and tumor weight were significantly reduced in rTCS-treated or rTCS/IL-2-treated nude mice bearing PC3 xenograft tumor compared with control. And significant difference was also found between rTCS and rTCS/IL-2 group. CONCLUSIONS: This study demonstrates that rTCS is a potential agent with high in vitro and in vivo anti-tumor activity on PC3 cells. And rTCS combined with IL-2 is a promising strategy in treating patients with prostate cancer in future.

Adaptive total variation-based spectral deconvolution with the split Bregman method.

Spectroscopic data often suffer from common problems of band overlap and noise. This paper presents a maximum a posteriori (MAP)-based algorithm for the band overlap problem. In the MAP framework, the likelihood probability density function (PDF) is constructed with Gaussian noise assumed, and the prior PDF is constructed with adaptive total variation (ATV) regularization. The split Bregman iteration algorithm is employed to optimize the ATV spectral deconvolution model and accelerate the speed of the spectral deconvolution. The main advantage of this algorithm is that it can obtain peak structure information as well as suppress noise simultaneity. Simulated and real spectra experiments manifest that this algorithm can satisfactorily recover the overlap peaks as well as suppress noise and are robust to the regularization parameter.

How social support influences learned helplessness in lung cancer patients: the chain mediation role of individual resilience and self-efficacy.

Background: Social support, which is a crucial external resource for cancer patients, was demonstrated to be a positive predictor of learned helplessness (LH). But it is far from clear whether and how social support decreases the LH in cancer patients. The purpose of present study is to detect the association between social support and LH and the role of individual resilience and self-efficacy in mediating this relationship. Methods: The convenience sampling method was utilized. From August 2022 to February 2024, a total of 537 lung cancer patients (M age = 60.25 years, SDage = 9.85 years) from five tertiary hospitals in one municipalities (Chongqing), and two provinces (Sichuan and Yunnan) were recruited, among which 389 were males and 148 were females. LH, social support, individual resilience, and self-efficacy were assessed by using standard scales. A structural equation model was constructed employing AMOS 23.0 to examine the interrelationships among social support, individual resilience, self-efficacy, and LH of lung cancer patients. Results: A total of 537 lung cancer patients were finally included. Social support, individual resilience, and self-efficacy were positively related to LH (r = -0.299 to -0.451, p < 0.01). The mediation model revealed that the direct effect of social support on LH was significant (ß = -0.407, p < 0.001). Besides, social support could also affect LH through three pathways: (1) the mediating effect of individual resilience (ß = -0.075, p < 0.001); (2) the mediating effect of self-efficacy (ß = -0.060, p < 0.05); (3) the chain mediating effect of individual resilience and self-efficacy (ß = -0.011, p < 0.05). Conclusion: The results indicate that social support alleviates lung cancer patients' LH, and that individual resilience and self-efficacy mediate the correlation between social support and LH. Besides providing adequate social support, intervention strategies built on individual resilience and self-efficacy should be applied to reduce LH in lung cancer patients.

Learned Helplessness and Associated Factors Among Patients with Lung Cancer.

Purpose: Learned helplessness (LH) is the psychological state in which an individual experiences multiple failures and setbacks and experiences a sense of loss when facing the current situation. It is a significant burden for lung cancer patients that can impair quality of life and lead to physical, social, and psychological difficulties. Thus, this study aimed to determine the level of LH among patients with lung cancer and identify factors associated with LH. Patients and Methods: From August 2022 to March 2023, 237 patients with lung cancer from Chongqing University Cancer Hospital were selected for this study. A general information questionnaire, the LH scale, the Brief Illness Perception questionnaire, the Strategies Used by People to Promote Health questionnaire, the Medical Coping Modes questionnaire, and the Self-esteem scale were used for the investigation. Multiple linear regression was employed to identify influencing factors for LH in patients with lung cancer. Results: The total LH score of patients with lung cancer was 52.19±11.20. Multiple linear regression analysis showed that illness perception (ß=0.249, P=0.001), self-efficacy (ß=-0.194, P=0.017), and resignation coping mode (ß=0.267, P<0.001) were the main influencing factors of LH (P<0.05), which explained 42.0% of the total variance. Conclusion: The score of LH in patients with lung cancer was at a moderate level in this study. Illness perception, self-efficacy, and resignation coping mode have been found to impact LH among patients with lung cancer. Healthcare professionals should implement effective interventions, such as promoting self-efficacy, encouraging positive coping, and reducing illness perception, to alleviate LH.

Influence of Financial Toxicity on the Quality of Life in Lung Cancer Patients Undergoing Immunotherapy: The Mediating Effect of Self-Perceived Burden.

Purpose: The purpose of this study is to understand the level of quality of life (QOL) of lung cancer patients receiving immunotherapy and to clarify the potential mediating role of self-perceived burden (SPB) in the relationship between financial toxicity (FT) and QOL. Patients and Methods: A convenience sample of 342 lung cancer patients receiving immunotherapy was recruited from a cancer hospital from October 2022 to April 2023 for this cross-sectional study. The participants were requested to complete the following structured questionnaires: a sociodemographic and clinical questionnaire, the Functional Assessment of Cancer Therapy-Lung (FACT-L), the Self-Perceived Burden Scale (SPBS) and the COmprehensive Score for Financial Toxicity (COST). The data were subjected to Pearson correlation analysis and bootstrapping analysis in structural equation modelling. Results: The total FACT-L score was 79.90±15.84 points in 322 lung cancer patients receiving immunotherapy. FT (ß = 0.37, P < 0.01) and SPB (ß = -0.27, P < 0.01) had a direct effect on QOL. In addition, SPB partly mediated the association between FT and QOL, and the standardized indirect effect was 0.19, accounting for 33.9% of the total effect. Conclusion: The present study revealed that there is still much room for improvement in the QOL of lung cancer patients during immunotherapy. A greater financial burden resulted in a greater self-perceived burden and was thus associated with inferior QOL. It is imperative for oncology nurses to routinely assess QOL, FT or risk and SPB for lung cancer patients undergoing immunotherapy as well as to assist those patients in understanding the potential financial risk of each choice and help them take more active roles in their routine clinical care.

A CD36-dependent non-canonical lipid metabolism program promotes immune escape and resistance to hypomethylating agent therapy in AML.

Environmental lipids are essential for fueling tumor energetics, but whether these exogenous lipids transported into cancer cells facilitate immune escape remains unclear. Here, we find that CD36, a transporter for exogenous lipids, promotes acute myeloid leukemia (AML) immune evasion. We show that, separately from its established role in lipid oxidation, CD36 on AML cells senses oxidized low-density lipoprotein (OxLDL) to prime the TLR4-LYN-MYD88-nuclear factor κB (NF-κB) pathway, and exogenous palmitate transfer via CD36 further potentiates this innate immune pathway by supporting ZDHHC6-mediated MYD88 palmitoylation. Subsequently, NF-κB drives the expression of immunosuppressive genes that inhibit anti-tumor T cell responses. Notably, high-fat-diet or hypomethylating agent decitabine treatment boosts the immunosuppressive potential of AML cells by hijacking CD36-dependent innate immune signaling, leading to a dampened therapeutic effect. This work is of translational interest because lipid restriction by US Food and Drug Administration (FDA)-approved lipid-lowering statin drugs improves the efficacy of decitabine therapy by weakening leukemic CD36-mediated immunosuppression.

Orientation Cues-Aware Facial Relationship Representation for Head Pose Estimation via Transformer.

Head pose estimation (HPE) is an indispensable upstream task in the fields of human-machine interaction, self-driving, and attention detection. However, practical head pose applications suffer from several challenges, such as severe occlusion, low illumination, and extreme orientations. To address these challenges, we identify three cues from head images, namely, critical minority relationships, neighborhood orientation relationships, and significant facial changes. On the basis of the three cues, two key insights on head poses are revealed: 1) intra-orientation relationship and 2) cross-orientation relationship. To leverage two key insights above, a novel relationship-driven method is proposed based on the Transformer architecture, in which facial and orientation relationships can be learned. Specifically, we design several orientation tokens to explicitly encode basic orientation regions. Besides, a novel token guide multi-loss function is accordingly designed to guide the orientation tokens as they learn the desired regional similarities and relationships. Experimental results on three challenging benchmark HPE datasets show that our proposed TokenHPE achieves state-of-the-art performance. Moreover, qualitative visualizations are provided to verify the effectiveness of the token-learning methodology.

Insights into Ultrasonication Treatment on the Characteristics of Cereal Proteins: Functionality, Conformational and Physicochemical Characteristics.

BACKGROUND: It would be impossible to imagine a country where cereals and their byproducts were not at the peak of foodstuff systems as a source of food, fertilizer, or for fiber and fuel production. Moreover, the production of cereal proteins (CPs) has recently attracted the scientific community's interest due to the increasing demands for physical wellbeing and animal health. However, the nutritional and technological enhancements of CPs are needed to ameliorate their functional and structural properties. Ultrasonic technology is an emerging nonthermal method to change the functionality and conformational characteristics of CPs. Scope and approach: This article briefly discusses the effects of ultrasonication on the characteristics of CPs. The effects of ultrasonication on the solubility, emulsibility, foamability, surface-hydrophobicity, particle-size, conformational-structure, microstructural, enzymatic-hydrolysis, and digestive properties are summarized. CONCLUSIONS: The results demonstrate that ultrasonication could be used to enhance the characteristics of CPs. Proper ultrasonic treatment could improve functionalities such as solubility, emulsibility, and foamability, and is a good method for altering protein structures (including surface hydrophobicity, sulfhydryl and disulfide bonds, particle size, secondary and tertiary structures, and microstructure). In addition, ultrasonic treatment could effectively promote the enzymolytic efficiency of CPs. Furthermore, the in vitro digestibility was enhanced after suitable sonication treatment. Therefore, ultrasonication technology is a useful method to modify cereal protein functionality and structure for the food industry.