Recent Advances in Immunotherapy for Breast Cancer: A Review.

Breast cancer is one of the most common malignant tumors in women in the world, and its incidence is increasing year by year, which seriously threatens the physical and mental health of women. Triple negative breast cancer (TNBC) is a special molecular type of breast cancer in which estrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 are negative. Compared with other molecular types of breast cancer, triple-negative breast cancer (TNBC) has high aggressiveness and metastasis, high recurrence rate, lack of effective therapeutic targets, and usually poor clinical treatment effect. Chemotherapy was the main therapeutic means used in the past. With the advent of the immune era, immunotherapy has made a lot of progress in the treatment of triple-negative breast cancer (TNBC), bringing new therapeutic hope for the treatment of triple-negative breast cancer. This review combines the results of cutting-edge medical research, mainly summarizes the research progress of immunotherapy, and summarizes the main treatment methods of triple-negative breast cancer (TNBC) immunotherapy, including immune checkpoint inhibitors, tumor vaccines, adoptive immunotherapy and the application of traditional Chinese and western medicine. It provides a new idea for the treatment of triple negative breast cancer (TNBC).

Exposure assessment to areca alkaloids in the Chinese populations through areca nut chewing.

Chewing areca nuts is popular in China. Areca alkaloids are the major toxic compounds in areca nuts. In this study, the levels of four areca alkaloids (i.e. arecoline, arecaidine, guvacoline and guvacine) in 119 areca nut samples were analyzed and 3030 areca nut consumption questionnaires were collected to investigate the exposure to areca alkaloids in the Chinese populations through areca nut chewing. The levels of arecoline, arecaidine, guvacoline and guvacine in different areca nut products were 0.46-4.97 mg/g, 0.57-7.51 mg/g, 0.08-1.44 mg/g and 0.03-8.48 mg/g, respectively. Chewing fresh areca fruits was the main source of arecoline and the total areca alkaloids exposure. The estimated daily intake (EDI) of arecoline and the total areca alkaloids for the Chinese populations were 1.126 and 2.625 mg/kg BW/day for average exposure, 4.411 and 9.739 mg/kg BW/day for high exposure (P95th). The EDI varied with age and gender. The young male population (≤ 34 years) had the highest EDI than other populations. Concentrated and focused efforts are required to educate the general public, especially the young male population, about the risks of areca nut chewing to reduce exposure to areca alkaloids of the Chinese population. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-024-05966-6.

Classification of anatomy and treatment approaches for aneurysms originating from the proximal of the A1 segment of the anterior cerebral artery in clinical settings.

Objective: To explore the spatial relationship between A1 segment proximal anterior cerebral artery aneurysms and their main trunks, classify them anatomically and develop targeted treatment strategies. Methods: This single-center retrospective analysis involved 39 patients diagnosed with aneurysms originating from the proximal of A1 segment of the anterior cerebral artery (2014-2023). Classify the patient's aneurysm into 5 types based on the location of the neck involving the carrier artery and the spatial relationship and projection direction of the aneurysm body with the carrier artery, and outcomes from treatment methods were compared. Results: Among 39 aneurysms, 18 cases underwent endovascular intervention treatment, including 6 cases of stent assisted embolization, 1 case of flow-diverter embolization, 5 cases of balloon assisted embolization, and 6 cases of simple coiling. At discharged, the mRS score of all endovascularly treated patients was 0, and the GOS score was 5 at 6 months after discharge. At discharge, the mRS score of microsurgical clipping treated patients was 0 for 15 cases, 3 for 1 case, 4 for 1 case and 5 for 2 cases. Six months after discharge, the GOS score was 5 for 16 cases, 4 for 2 cases, 3 for 2 cases, and 1 for 1 case. GOS outcomes at 6 months were better for endovascularly treated patients (p = 0.047). Conclusion: Results showed better outcomes for the endovascular treatment group compared to microsurgical clipping at 6 months after surgery. The anatomical classification of aneurysms in this region may be of help to develop effective treatment strategies.

Stability, bifurcation, and chaos in a class of scalar quartic polynomial delay systems.

In this paper, a class of scalar quartic polynomial delay systems is investigated. We found rich dynamics in this system through numerical simulation, including chaotic attractors, chaotic saddles, and intermittent chaos. Moreover, this chaotic quartic system may serve as an approximation, through Taylor expansion, for a wide class of scalar delay differential equations. Thus, these nonlinear systems may exhibit chaotic behaviors, and the studies in our paper may provide an insight into the emergence of chaos in other time-delay nonlinear systems. We also conduct a detailed theoretical analysis of the system, including the stability of equilibria and Hopf bifurcation analysis based on the theory of normal form and center manifold. Additionally, a numerical analysis is provided to give numerical evidence for the existence of chaos.

Graph Embedding Interclass Relation-Aware Adaptive Network for Cross-Scene Classification of Multisource Remote Sensing Data.

The unsupervised domain adaptation (UDA) based cross-scene remote sensing image classification has recently become an appealing research topic, since it is a valid solution to unsupervised scene classification by exploiting well-labeled data from another scene. Despite its good performance in reducing domain shifts, UDA in multisource data scenarios is hindered by several critical challenges. The first one is the heterogeneity inherent in multisource data complicates domain alignment. The second challenge is the incomplete representation of feature distribution caused by the neglect of the contribution from global information. The third challenge is the inaccuracies in alignment due to errors in establishing target domain conditional distributions. Since UDA does not guarantee the complete consistency of the distribution of the two domains, networks using simple classifiers are still affected by domain shifts, resulting in poor performance. In this paper, we propose a graph embedding interclass relation-aware adaptive network (GeIraA-Net) for unsupervised classification of multi-source remote sensing data, which facilitates knowledge transfer at the class level for two domains by leveraging aligned features to perceive inter-class relation. More specifically, a graph-based progressive hierarchical feature extraction network is constructed, capable of capturing both local and global features of multisource data, thereby consolidating comprehensive domain information within a unified feature space. To deal with the imprecise alignment of data distribution, a joint de-scrambling alignment strategy is designed to utilize the features obtained by a three-step pseudo-label generation module for more delicate domain calibration. Moreover, an adaptive inter-class topology based classifier is constructed to further improve the classification accuracy by making the classifier domain adaptive at the category level. The experimental results show that GeIraA-Net has significant advantages over the current state-of-the-art cross-scene classification methods.

A Thermally Populated Germylene-Based Donor-Acceptor Diradical.

This work reports synthesis of a germylene based donor-acceptor molecule and its thermal excitation to a triplet state by coordination with a Lewis acid. Products have been characterized by single crystal X-ray diffraction, EPR spectroscopy, and SQUID measurement, in conjunction with DFT calculation. The singlet-triplet energy gap of the donor-acceptor molecule is dramatically reduced from -18.8 to -7.2 kcal/mol by the coordination with B(C6F5)3 (BCF), which enables an intramolecular single electron transfer from one germylene moiety to another upon heating, forming an intramolecular radical ion pair with diradical character. The work provides an approach to the formation of thermally populated open-shell species of heavier main group elements.

Solution-Processable MOF-on-MOF System Constructed via Template-Assisted Growth for Ultratrace H2S Detection.

Conductive metal-organic frameworks (c-MOFs) hold promise for highly sensitive sensing systems due to their conductivity and porosity. However, the fabrication of c-MOF thin films with controllable morphology, thickness, and preferential orientation remains a formidable yet ubiquitous challenge. Herein, we propose an innovative template-assisted strategy for constructing MOF-on-MOF (Ni3(HITP)2/NUS-8 (HITP: 2,3,6,7,10,11-hexamino-tri(p-phenylene))) systems with good electrical conductivity, porosity, and solution processability. Leveraging the 2D nature and solution processability of NUS-8, we achieve the controllable self-assembly of Ni3(HITP)2 on NUS-8 nanosheets, producing solution-processable Ni3(HITP)2/NUS-8 nanosheets with a film conductivity of 1.55 × 10-3 S·cm-1 at room temperature. Notably, the excellent solution processability facilitates the fabrication of large-area thin films and printing of intricate patterns with good uniformity, and the Ni3(HITP)2/NUS-8-based system can monitor finger bending. Gas sensors based on Ni3(HITP)2/NUS-8 exhibit high sensitivity (LOD ~ 6 ppb) and selectivity towards ultratrace H2S at room temperature, attributed to the coupling between Ni3(HITP)2 and NUS-8 and the redox reaction with H2S. This approach not only unlocks the potential of stacking different MOF layers in a sequence to generate functionalities that cannot be achieved by a single MOF, but also provides novel avenues for the scalable integration of MOFs in miniaturized devices with salient sensing performance.

Tumor-Associated Antigen Burden Correlates with Immune Checkpoint Blockade Benefit in Tumors with Low Levels of T-cell Exhaustion.

Tumor-associated antigens (TAAs) are important targets for cancer vaccines. However, TAA-based vaccines have not yet achieved their full potential in clinical trials. In contrast, immune checkpoint blockade (ICB) has emerged as an effective therapy, leading to durable responses in selected cancer patients. To date, few generalizable associations between TAAs and ICB benefit have been reported, with most studies focusing on melanoma that has the highest mutation rate in cancer. In this study, we developed a TAA burden (TAB) algorithm based on known and putative TAAs and investigated the association of TAB with ICB benefit. Analysis of the IMVigor210 patient cohort of urothelial carcinoma treated with anti-PD-L1 revealed that high tumor mutation burden (TMB) weakened the association of TAB with ICB benefit. Furthermore, TAB correlated with ICB efficacy in tumors characterized by negative PD-L1 staining on immune cells, while high levels of PD-L1 staining on immune cells were linked to T-cell exhaustion. Validation across independent clinical datasets-including urothelial carcinoma cohorts treated with anti-PD1/PD-L1 agents and neoadjuvant anti-PD1 trials for head and neck cancers-corroborated the finding that TAB correlates with ICB benefit in tumors with low T-cell exhaustion. Pan-cancer analyses revealed that in most cancer entities, tumors with higher T-cell exhaustion exhibited lower TAB levels, implying possible immunoediting of TAAs in tumors with established antitumor immunity. Our study challenges the prevailing notion of a lack of association between TAAs and ICB response. It also underscores the need for future investigations into the immunogenicity of TAAs and TAA-based vaccine strategies in tumors with low levels of T-cell exhaustion.

Visualization and standardized quantification of surface charge density for triboelectric materials.

Triboelectric nanogenerator (TENG) operates on the principle of utilizing contact electrification and electrostatic induction. However, visualization and standardized quantification of surface charges for triboelectric materials remain challenging. Here, we report a surface charge visualization and standardized quantification method using electrostatic surface potential measured by Kevin probe and the iterative regularization strategy. Moreover, a tuning strategy on surface charge is demonstrated based on the corona discharge with a three-electrode design. The long-term stability and dissipation mechanisms of the injected negative or positive charges demonstrate high dependence on deep carrier traps in triboelectric materials. Typically, we achieved a 70-fold enhancement on the output voltage (~135.7 V) for the identical polytetrafluoroethylene (PTFE) based TENG (neg-PTFE/PTFE or posi-PTFE/PTFE triboelectric pair) with stable surface charge density (5% decay after 140 days). The charged PTFE was demonstrated as a robot e-skins for non-contact perception of object geometrics. This work provides valuable tools for surface charge visualization and quantification, giving a new strategy for a deeper understanding of contact electrification.

Pulsatilla decoction alleviates DSS-induced UC by activating FXR-ASBT pathways to ameliorate disordered bile acids homeostasis.

Ethnopharmacological relevance: Pulsatilla decoction (PD) is a classical prescription for the treatment of ulcerative colitis. Previous studies have demonstrated that the therapeutic efficacy of PD is closely associated with the activation of Farnesoid X receptor (FXR). The activity of FXR is regulated by apical sodium-dependent bile acid transporter (ASBT), and the FXR-ASBT cascade reaction, centered around bile acid receptor FXR, plays a pivotal role in maintaining bile acid metabolic homeostasis to prevent the occurrence and progression of ulcerative colitis (UC). Aim of the study: To elucidate the underlying mechanism by which PD exerts its proteactive effects against Dextran Sulfate Sodium Salt (DSS)-induced ulcerative colitis, focusing on the modulation of FXR and ASBT. Materials and methods: To establish a model of acute ulcerative colitis, BALB/C mice were administered 3.5% DSS in their drinking water for consecutive 7 days. The disease activity index (DAI) was employed to evaluate the clinical symptoms exhibited by each group of mice. Goblet cell expression in colon tissue was assessed using glycogen schiff periodic acid-Schiff (PAS) and alcian blue staining techniques. Inflammatory cytokine expression in serum and colonic tissues was examined through enzyme-linked immunosorbent assay (ELISA). A PCR Array chip was utilized to screen 88 differential genes associated with the FXR-ASBT pathway in UC treatment with PD. Western blotting (WB) analysis was performed to detect protein expression levels of differentially expressed genes in mouse colon tissue. Results: The PD treatment effectively reduced the Disease Activity Index (DAI) score and mitigated colon histopathological damage, while also restoring weight and colon length. Furthermore, it significantly alleviated the severity of ulcerative colitis (UC), regulated inflammation, modulated goblet cell numbers, and restored bile acid balance. Additionally, a PCR Array analysis identified 21 differentially expressed genes involved in the FXR-ASBT pathway. Western blot results demonstrated significant restoration of FXR, GPBAR1, CYP7A1, and FGF15 protein expression levels following PD treatment; moreover, there was an observed tendency towards increased expression levels of ABCB11 and RXRα. Conclusion: The therapeutic efficacy of PD in UC mice is notable, potentially attributed to its modulation of bile acid homeostasis, enhancement of gut barrier function, and attenuation of intestinal inflammation.

Mechanism of Lian Hua Qing Wen capsules regulates the inflammatory response caused by M1 macrophage based on cellular experiments and computer simulations.

PURPOSE: The polarization of macrophages with the resulting inflammatory response play a crucial part in tissue and organ damage due to inflammatory. Study has proved Lian Hua Qing Wen capsules (LHQW) can reduce activation of inflammatory response and damage of tissue derived from the inflammatory reactions. However, the mechanism of LHQW regulates the macrophage-induced inflammatory response is unclear. Therefore, we investigated the mechanism of LHQW regulated the inflammatory response of M1 macrophages by cellular experiments and computer simulations. METHODS: This study has analysed the targets and mechanisms of macrophage regulating inflammatory response at gene and protein levels through bioinformatics. The monomeric components of LHQW were analyzed by High Performance Liquid Chromatography (HPLC). We established the in vitro cell model by M1 macrophages (Induction of THP-1 cells into M1 macrophages). RT-qPCR and immunofluorescence were used to detect changes in gene and protein levels of key targets after LHQW treatment. Computer simulations were utilized to verify the binding stability of monomeric components and protein targets. RESULTS: Macrophages had 140,690 gene targets, inflammatory response had 12,192 gene targets, intersection gene targets were 11,772. Key monomeric components (including: Pinocembrin, Fargesone-A, Nodakenin and Bowdichione) of LHQW were screened by HPLC. The results of cellular experiments indicated that LHQW could significantly reduce the mRNA expression of CCR5, CSF2, IFNG and TNF, thereby alleviating the inflammatory response caused by M1 macrophage. The computer simulations further validated the binding stability and conformation of key monomeric components and key protein targets, and IFNG/Nodakenin was able to form the most stable binding conformation for its action. CONCLUSION: In this study, the mechanism of LHQW inhibits the polarization of macrophages and the resulting inflammatory response was investigated by computer simulations and cellular experiments. We found that LHQW may not only reduce cell damage and death by acting on TNF and CCR5, but also inhibit the immune recognition process and inflammatory response by regulating CSF2 and IFNG to prevent polarization of macrophages. Therefore, these results suggested that LHQW may act through multiple targets to inhibit the polarization of macrophages and the resulting inflammatory response.

What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years.

BACKGROUND: Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures. AIM: To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research. METHODS: We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide. RESULTS: Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence. CONCLUSION: Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

Predicting bond dissociation energies of cyclic hypervalent halogen reagents using DFT calculations and graph attention network model.

Although hypervalent iodine(III) reagents have become staples in organic chemistry, the exploration of their isoelectronic counterparts, namely hypervalent bromine(III) and chlorine(III) reagents, has been relatively limited, partly due to challenges in synthesizing and stabilizing these compounds. In this study, we conduct a thorough examination of both homolytic and heterolytic bond dissociation energies (BDEs) critical for assessing the chemical stability and functional group transfer capability of cyclic hypervalent halogen compounds using density functional theory (DFT) analysis. A moderate linear correlation was observed between the homolytic BDEs across different halogen centers, while a strong linear correlation was noted among the heterolytic BDEs across these centers. Furthermore, we developed a predictive model for both homolytic and heterolytic BDEs of cyclic hypervalent halogen compounds using machine learning algorithms. The results of this study could aid in estimating the chemical stability and functional group transfer capabilities of hypervalent bromine(III) and chlorine(III) reagents, thereby facilitating their development.

Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment.

Background: Anoikis is a form of programmed cell death essential for preventing cancer metastasis. In some solid cancer, anoikis resistance can facilitate tumor progression. However, this phenomenon is underexplored in clear-cell renal cell carcinoma (ccRCC). Methods: Using SVM machine learning, we identified core anoikis-related genes (ARGs) from ccRCC patient transcriptomic data. A LASSO Cox regression model stratified patients into risk groups, informing a prognostic model. GSVA and ssGSEA assessed immune infiltration, and single-cell analysis examined ARG expression across immune cells. Quantitative PCR and immunohistochemistry validated ARG expression differences between immune therapy responders and non-responders in ccRCC. Results: ARGs such as CCND1, CDKN3, PLK1, and BID were key in predicting ccRCC outcomes, linking higher risk with increased Treg infiltration and reduced M1 macrophage presence, indicating an immunosuppressive environment facilitated by anoikis resistance. Single-cell insights showed ARG enrichment in Tregs and dendritic cells, affecting immune checkpoints. Immunohistochemical analysis reveals that ARGs protein expression is markedly elevated in ccRCC tissues responsive to immunotherapy. Conclusion: This study establishes a novel anoikis resistance gene signature that predicts survival and immunotherapy response in ccRCC, suggesting that manipulating the immune environment through these ARGs could improve therapeutic strategies and prognostication in ccRCC.

Production of constrained L-cyclo-tetrapeptides by epimerization-resistant direct aminolysis.

The synthesis of constrained 12-membered rings is notably difficult. The main challenges result from constraints during the linear peptide cyclization. Attempts to overcome constraints through excessive activation frequently cause peptidyl epimerization, while insufficient activation of the C-terminus hampers cyclization and promotes intermolecular oligomer formation. We present a ß-thiolactone framework that enables the synthesis of cyclo-tetrapeptides via direct aminolysis. This tactic utilizes a mechanism that restricts C-terminal carbonyl rotation while maintaining high reactivity, thereby enabling efficient head-to-tail amidation, reducing oligomerization, and preventing epimerization. A broad range of challenging cyclo-tetrapeptides ( > 20 examples) are synthesized in buffer and exhibits excellent tolerance toward nearly all proteinogenic amino acids. Previously unattainable macrocycles, such as cyclo-L-(Pro-Tyr-Pro-Val), have been produced and identified as µ-opioid receptor (MOR) agonists, with an EC50 value of 2.5 nM. Non-epimerizable direct aminolysis offers a practical solution for constrained peptide cyclization, and the discovery of MOR agonist activity highlights the importance of overcoming synthetic challenges for therapeutic development.

AHNAK2 Regulates NF-κB/MMP-9 Signaling to Promote Pancreatic Cancer Progression.

Early metastasis of pancreatic cancer (PaC) is a major cause of its high mortality rate. Previous studies have shown that AHNAK2 is involved in the progression of some tumors and is predicted to be an independent prognostic factor for PaC; however, the specific mechanisms through which AHNAK2 regulates PaC remain unclear. In this study, we examined the role of AHNAK2 in PaC and its potential molecular mechanisms. AHNAK2 mRNA and protein expression in PaC tissues and cells were measured using qRT-PCR and western blot analysis. After AHNAK2 knockdown using small interfering RNA, PaC cells were subjected to CCK-8 scratch, and Transwell assays to assess cell proliferation, migration, and invasion, respectively. Furthermore, the validation of the mechanistic pathway was achieved by western blot analysis. AHNAK2 mRNA and protein levels were up-regulated in PaC and silencing AHNAK2 significantly inhibited the proliferation, migration, and invasion of PaC cells. Mechanistically, AHNAK2 knockdown decreased the expression of phosphorylated p65, phosphorylated IκBα, and matrix metalloproteinase-9 (MMP-9), suggesting that activation of the NF-κB/MMP-9 signaling pathway was inhibited. Importantly, activation of NF-κB reversed the effects of AHNAK2 knockdown. Our findings indicate that AHNAK2 promotes PaC progression through the NF-kB/MMP-9 pathway and provides a theoretical basis for targeting AHNAK2 for the treatment of PaC.

Observation of quantum nonlocality in Greenberger-Horne-Zeilinger entanglement on a silicon chip.

Nonlocality is the defining feature of quantum entanglement. Entangled states with multiple particles are of crucial importance in fundamental tests of quantum physics as well as in many quantum information tasks. One of the archetypal multipartite quantum states, Greenberger-Horne-Zeilinger (GHZ) state, allows one to observe the striking conflict of quantum physics to local realism in the so-called all-versus-nothing way. This is profoundly different from Bell's theorem for two particles, which relies on statistical predictions. Here, we demonstrate an integrated photonic chip capable of generating and manipulating the four-photon GHZ state. We perform a complete characterization of the four-photon GHZ state using quantum state tomography and obtain a state fidelity of 0.729±0.006. We further use the all-versus-nothing test and the Mermin inequalities to witness the quantum nonlocality of GHZ entanglement. Our work paves the way to perform fundamental tests of quantum physics with complex integrated quantum devices.

A Principle Design of Registration-Fusion Consistency: Toward Interpretable Deep Unregistered Hyperspectral Image Fusion.

For hyperspectral image (HSI) and multispectral image (MSI) fusion, it is often overlooked that multisource images acquired under different imaging conditions are difficult to be perfectly registered. Although some works attempt to fuse unregistered images, two thorny challenges remain. One is that registration and fusion are usually modeled as two independent tasks, and there is no yet a unified physical model to tightly couple them. Another is that deep learning (DL)-based methods may lack sufficient interpretability and generalization. In response to the above challenges, we propose an unregistered HSI fusion framework energized by a unified model of registration and fusion. First, a novel registration-fusion consistency physical perception model (RFCM) is designed, which uniformly models the image registration and fusion problem to greatly reduce the sensitivity of fusion performance to registration accuracy. Then, an HSI fusion framework (MoE-PNP) is proposed to learn the knowledge reasoning process for solving RFCM. Each basic module of MoE-PNP one-to-one corresponds to the operation in the optimization algorithm of RFCM, which can ensure clear interpretability of the network. Moreover, MoE-PNP captures the general fusion principle for different unregistered images and therefore has good generalization. Extensive experiments demonstrate that MoE-PNP achieves state-of-the-art performance for unregistered HSI and MSI fusion. The code is available at https://github.com/Jiahuiqu/MoE-PNP.