Enhanced fluorescence properties of polyfluorene-based polymer dots through an ascorbic acid-photoaging treatment for living cell imaging.

The polymer dots (Pdots) prepared by the conjugated polymer (PFO, poly (9,9-dihexylfluorene-2,7-diyl)) have high fluorescence intensity and are often used in biological fluorescence imaging. However, due to the chain defects, the PFO Pdots suffer from stability issues such as photoinactivation and photobleaching. To solve this problem, we drew inspiration from the preparation process of organic planar light-emitting devices and added an optimization processing after Pdots was prepared. We used illumination as the driving force to activate defects on its chain, and ascorbic acid as a reducing substance to restore the chain defects of the polymer to a more stable state. Through this method, we increased the fluorescence intensity by nearly 1.9 times, and significantly improving their long and short-term stability. In addition, it ensures other properties remain unchanged. This optimization scheme is also fully compatible with the entire biological imaging process, ensuring that other important properties such as cytotoxicity do not undergo unnecessary changes. Furthermore, we conducted material characterization and theoretical simulation, revealing that the optimization scheme mainly serves to repair C-9 alkyl defects on the polyfluorene unit. This study has improved and enhanced the fluorescence performance of PFO Pdots, and also provides a way to optimize the treatment of other similar conjugated polymer material systems.

Tumor cell-released autophagosomes (TRAPs) induce PD-L1-decorated NETs that suppress T-cell function to promote breast cancer pulmonary metastasis.

BACKGROUND: Lung metastasis is the primary cause of breast cancer-related mortality. Neutrophil extracellular traps (NETs) are involved in the progression of breast cancer. However, the mechanism of NET formation is not fully understood. This study posits that tumor cell-released autophagosomes (TRAPs) play a crucial role in this process. METHODS: TRAPs were isolated from breast cancer cell lines to analyze their impact on NET formation in both human and mouse neutrophils. The study used both in vitro and in vivo models, including Toll-like receptor 4 (TLR4-/-) mice and engineered breast cancer cell lines. Immunofluorescence, ELISA, Western blotting, RNA sequencing, and flow cytometry were employed to dissect the signaling pathways leading to NET production and to explore their immunosuppressive effects, particularly focusing on the impact of NETs on T-cell function. The therapeutic potential of targeting TRAP-induced NETs and their immunosuppressive functions was evaluated using DNase I and αPD-L1 antibodies. Clinical relevance was assessed by correlating circulating levels of TRAPs and NETs with lung metastasis in patients with breast cancer. RESULTS: This study showed that TRAPs induced the formation of NETs in both human and mouse neutrophils by using the high mobility group box 1 and activating the TLR4-Myd88-ERK/p38 signaling axis. More importantly, PD-L1 carried by TRAP-induced NETs inhibited T-cell function in vitro and in vivo, thereby contributing to the formation of lung premetastatic niche (PMN) immunosuppression. In contrast, Becn1 KD-4T1 breast tumors with decreased circulating TRAPs in vivo reduced the formation of NETs, which in turn attenuated the immunosuppressive effects in PMN and resulted in a reduction of breast cancer pulmonary metastasis in murine models. Moreover, treatment with αPD-L1 in combination with DNase I that degraded NETs restored T-cell function and significantly reduced tumor metastasis. TRAP levels in the peripheral blood positively correlated with NET levels and lung metastasis in patients with breast cancer. CONCLUSIONS: Our results demonstrate a novel role of TRAPs in the formation of PD-L1-decorated NETs, which may provide a new strategy for early detection and treatment of pulmonary metastasis in patients with breast cancer.

The meta-learning method for the ensemble model based on situational meta-task.

Introduction: The meta-learning methods have been widely used to solve the problem of few-shot learning. Generally, meta-learners are trained on a variety of tasks and then generalized to novel tasks. Methods: However, existing meta-learning methods do not consider the relationship between meta-tasks and novel tasks during the meta-training period, so that initial models of the meta-learner provide less useful meta-knowledge for the novel tasks. This leads to a weak generalization ability on novel tasks. Meanwhile, different initial models contain different meta-knowledge, which leads to certain differences in the learning effect of novel tasks during the meta-testing period. Therefore, this article puts forward a meta-optimization method based on situational meta-task construction and cooperation of multiple initial models. First, during the meta-training period, a method of constructing situational meta-task is proposed, and the selected candidate task sets provide more effective meta-knowledge for novel tasks. Then, during the meta-testing period, an ensemble model method based on meta-optimization is proposed to minimize the loss of inter-model cooperation in prediction, so that multiple models cooperation can realize the learning of novel tasks. Results: The above-mentioned methods are applied to popular few-shot character datasets and image recognition datasets. Furthermore, the experiment results indicate that the proposed method achieves good effects in few-shot classification tasks. Discussion: In future work, we will extend our methods to provide more generalized and useful meta-knowledge to the model during the meta-training period when the novel few-shot tasks are completely invisible.

Cellulose separation from ramie bone by one step process with green hydrogen peroxide-citric acid.

Ramie bone (RB), an agricultural waste generated in the textile industry, is a vastly productive renewable natural resource with the potential to be used as a source of cellulose. In this study, ramie bone cellulose (RB-CE) was obtained in one step using a simple and ecologically friendly hydrogen peroxide-citric acid (HPCA) treatment procedure that avoided the use of halogenated reagents and strong acids while also streamlining the treatment processes. Various analytical methods were used to investigate the chemical composition and structure, crystallinity, morphology, thermal properties, surface area and hydration properties of cellulose separated at different treatment temperatures. HPCA successfully removed lignin and hemicellulose from RB, according to chemical composition analysis and FTIR. RB-CE had a type I cellulose crystal structure, and the crystallinity improved with increasing treatment temperature, reaching 72.51 % for RB-CE90. The RB-CE showed good thermal stability with degradation temperatures ranging from 294.2 °C to 319.1 °C. Furthermore, RB-CE had a high water/oil binding capacity, with RB-CE90 having WHC and OBC of 9.68 g/g and 7.24 g/g, respectively. The current work serves as a model for the environmentally friendly and convenient extraction of cellulose from biomass, and the cellulose obtained can be employed in the field of food and composite materials.

Codeposition Enhances the Performance of Electrochemical Aptamer-Based Sensors.

Electrochemical aptamer-based (EAB) sensors, a minimally invasive means of performing high-frequency, real-time measurement of drugs and biomarkers in situ in the body, have traditionally been fabricated by depositing their target-recognizing aptamer onto an interrogating gold electrode using a "sequential" two-step method involving deposition of the thiol-modified oligonucleotide (typically for 1 h) followed by incubation in mercaptohexanol solution (typically overnight) to complete the formation of a stable, self-assembled monolayer. Here we use EAB sensors targeting vancomycin, tryptophan, and phenylalanine to show that "codeposition", a less commonly employed EAB fabrication method in which the thiol-modified aptamer and the mercaptohexanol diluent are deposited on the electrode simultaneously and for as little as 1 h, improves the signal gain (relative change in signal upon the addition of high concentrations of the target) of the vancomycin and tryptophan sensors without significantly reducing their stability. In contrast, the gain of the phenylalanine sensor is effectively identical irrespective of the fabrication approach employed. This sensor, however, appears to employ binding-induced displacement of the redox reporter rather than binding-induced folding as its signal transduction mechanism, suggesting in turn a mechanism for the improvement observed for the other two sensors. Codeposition thus not only provides a more convenient means of fabricating EAB sensors but also can improve their performance.

Semiconducting polymer dots for multifunctional integrated nanomedicine carriers.

The expansion applications of semiconducting polymer dots (Pdots) among optical nanomaterial field have long posed a challenge for researchers, promoting their intelligent application in multifunctional nano-imaging systems and integrated nanomedicine carriers for diagnosis and treatment. Despite notable progress, several inadequacies still persist in the field of Pdots, including the development of simplified near-infrared (NIR) optical nanoprobes, elucidation of their inherent biological behavior, and integration of information processing and nanotechnology into biomedical applications. This review aims to comprehensively elucidate the current status of Pdots as a classical nanophotonic material by discussing its advantages and limitations in terms of biocompatibility, adaptability to microenvironments in vivo, etc. Multifunctional integration and surface chemistry play crucial roles in realizing the intelligent application of Pdots. Information visualization based on their optical and physicochemical properties is pivotal for achieving detection, sensing, and labeling probes. Therefore, we have refined the underlying mechanisms and constructed multiple comprehensive original mechanism summaries to establish a benchmark. Additionally, we have explored the cross-linking interactions between Pdots and nanomedicine, potential yet complete biological metabolic pathways, future research directions, and innovative solutions for integrating diagnosis and treatment strategies. This review presents the possible expectations and valuable insights for advancing Pdots, specifically from chemical, medical, and photophysical practitioners' standpoints.

Respiratory protein-driven selectivity during the Permian-Triassic mass extinction.

Extinction selectivity determines the direction of macroevolution, especially during mass extinction; however, its driving mechanisms remain poorly understood. By investigating the physiological selectivity of marine animals during the Permian-Triassic mass extinction, we found that marine clades with lower O2-carrying capacity hemerythrin proteins and those relying on O2 diffusion experienced significantly greater extinction intensity and body-size reduction than those with higher O2-carrying capacity hemoglobin or hemocyanin proteins. Our findings suggest that animals with high O2-carrying capacity obtained the necessary O2 even under hypoxia and compensated for the increased energy requirements caused by ocean acidification, which enabled their survival during the Permian-Triassic mass extinction. Thus, high O2-carrying capacity may have been crucial for the transition from the Paleozoic to the Modern Evolutionary Fauna.

Proposed mechanisms of electron uptake in metal-corroding methanogens and their potential for CO2 bioconversion applications.

Some methanogens are electrotrophic bio-corroding microbes that can acquire electrons from solid surfaces including metals. In the laboratory, pure cultures of methanogenic cells oxidize iron-based materials including carbon steel, stainless steel, and Fe0. For buried or immersed pipelines or other metallic structures, methanogens are often major components of corroding biofilms with complex interspecies relationships. Models explaining how these microbes acquire electrons from solid donors are multifaceted and include electron transfer via redox mediators such as H2 or by direct contact through membrane proteins. Understanding the electron uptake (EU) routes employed by corroding methanogens is essential to develop efficient strategies for corrosion prevention. It is also beneficial for the development of bioenergy applications relying on methanogenic EU from solid donors such as bioelectromethanogenesis, hybrid photosynthesis, and the acceleration of anaerobic digestion with electroconductive particles. Many methanogenic species carrying out biocorrosion are the same ones forming the extensive abiotic-biological interfaces at the core of these bio-applications. This review will discuss the interactions between corrosive methanogens and metals and how the EU capability of these microbes can be harnessed for different sustainable biotechnologies.

Recent advances in biological molecule detection based on a three-dimensional graphene structure.

Graphene has become an attractive material in the field of electrochemical detection owing to its unique electrical properties. Although the simple stacking structures of two-dimensional (2D) graphene sheets can provide excellent detection properties, a macroscopic three-dimensional (3D) structure needs to be constructed to enhance its functional properties. Graphene with a 3D structure has elegant functions, unlike graphene with a 2D structure. These properties include a large specific surface area, easy loading of nanomaterials with electrocatalytic and redox functions, and so on. Herein, we outline the preparation methods (self-assembly, chemical vapor deposition, templates, and 3D printing) for 3D graphene structures for obtaining excellent detection performance and applications in detecting biological molecules, bacteria, and cells. Furthermore, this review focuses on the improvement of the detection performance and enhancement of the applicability of graphene-based electrochemical sensors. We hope that this article will provide a reference for the future development of electrochemical sensors based on 3D graphene composites.

High-Affinity Aptamers for In Vitro and In Vivo Cocaine Sensing.

The ability to quantify cocaine in biological fluids is crucial for both the diagnosis of intoxication and overdose in the clinic as well as investigation of the drug's pharmacological and toxicological effects in the laboratory. To this end, we have performed high-stringency in vitro selection to generate DNA aptamers that bind cocaine with nanomolar affinity and clinically relevant specificity, thus representing a dramatic improvement over the current-generation, micromolar-affinity, low-specificity cocaine aptamers. Using these novel aptamers, we then developed two sensors for cocaine detection. The first, an in vitro fluorescent sensor, successfully detects cocaine at clinically relevant levels in 50% human serum without responding significantly to other drugs of abuse, endogenous substances, or a diverse range of therapeutic agents. The second, an electrochemical aptamer-based sensor, supports the real-time, seconds-resolved measurement of cocaine concentrations in vivo in the circulation of live animals. We believe the aptamers and sensors developed here could prove valuable for both point-of-care and on-site clinical cocaine detection as well as fundamental studies of cocaine neuropharmacology.

An effective route to the additive manufacturing of a mechanically gradient supramolecular polymer nanocomposite structure.

3D Printing techniques are additive methods of fabricating parts directly from computer-aided designs. Whilst the clearest benefit is the realisation of geometrical freedom, multi-material printing allows the introduction of compositional variation and highly tailored product functionality. The paper reports a proof-of-concept additive manufacturing study to deposit a supramolecular polymer and a complementary organic filler to form composites with gradient composition to enable spatial distribution of mechanical properties and functionality by tuning the number of supramolecular interactions. We use a dual-feed extrusion 3D printing process, with feed stocks based on the supramolecular polymer and its organic composite, delivered at ratios predetermined. This allows for production of a graded specimen with varying filler concentration that dictates the mechanical properties. The printed specimen was inspected under dynamic load in a tensile test using digital image correlation to produce full-field deformation maps, which showed clear differences in deformation in regions with varying compositions, corresponding to the designed-in variations. This approach affords a novel method for printing material with graded mechanical properties which are not currently commercially available or easily accessible, however, the method can potentially be directly translated to the generation of biomaterial-based composites featuring gradients of mechanical properties.

PERSISTENT SUBRETINAL FLUID AFTER VITRECTOMY FOR MACULAR HOLE-ASSOCIATED RETINAL DETACHMENT.

PURPOSE: To evaluate the incidence, associated factors, and outcome of persistent subretinal fluid (SRF) after vitrectomy for macular hole-associated retinal detachment (MHRD). METHODS: A total of 158 eyes from 156 patients with MHRD who achieved macular hole closure after primary vitrectomy were included in the analysis; persistent SRF was defined as the presence of SRF for more than 1 month after first surgery. Preoperative and postoperative parameters were analyzed for their relationship with SRF development. RESULTS: Persistent SRF was observed in 19 eyes (12.0% of 158) postoperatively. Seven eyes (36.8% of 19) with persistent SRF eventually displayed complete absorption during follow-up. Univariate analysis revealed that eyes with persistent SRF were statistically associated with internal limiting membrane inverted flap, duration of symptoms, tamponade (perfluoropropane/silicone oil: 14/5 vs. 35/104, P < 0.001), and MHRD subtype (Type 1/Type 2/Type 3: 15/4/0 vs. 60/40/39, P = 0.003). In multivariate analysis, only internal limiting membrane inverted flap (odds ratio, 15.778, 95% confidence interval, 3.170-78.523; P = 0.001) was positively associated with persistent SRF. There were no significant differences in best-corrected visual acuity improvement ( P = 0.425) between the SRF involved foveal and without involved foveal groups and no significant differences between the SRF complete absorption and incomplete absorption groups. CONCLUSION: Absorption of persistent SRF may be more difficult in MHRD eyes than in ordinary rhegmatogenous retinal detachment eyes. The internal limiting membrane inverted flap in MHRD was associated with a greater likelihood of persistent SRF. The location and incomplete absorption of persistent SRF did not seem to be associated with the final visual outcome.

Improving biomass yields of microalgae biofilm by coculturing two microalgae species via forming biofilms with uniform microstructures and small cell-clusters.

Microalgae coculture has the potential to promote microalgae biofilm growth. Herein, three two-species cocultured biofilms were studied by determining biomass yields and detailed microstructure parameters, including porosity, average pore length, average cluster length, etc. It was found that biomass yields could reduce by 21-53 % when biofilm porosities decreased from about 35 % to 20 %; while at similar porosities (∼20 %), biomass yields of cocultured biofilms increased by 37 % when they possessed uniform microstructure and small cell-clusters (pores and clusters of 1 âˆ¼ 10 µm accounted for 96 % and 68 %, respectively). By analyzing morphologies and surface properties of cells, it was found that cells with small size, spherical shape, and reduced surface polymers could hinder the cell-clusters formation, thereby promoting biomass yields. The study provides new insights into choosing cocultured microalgae species for improving the biomass yield of biofilm via manipulating biofilm microstructures.

Use microalgae to treat coke wastewater for producing biofuel: Influence of phenol on photosynthetic properties and intracellular components of microalgae.

Using microalgae to treat coking wastewater has important application prospects and environmental significance. Previous studies have suggested that phycoremediation of pollutants from coking wastewater is feasible and can potentially enhance biodiesel production. This work investigates the effects of phenol in coking wastewater on C. pyrenoidosa and S. obliquus growth, photosynthesis activity, and intracellular components. The results indicated that when the phenol concentration was lower than 300 mg L-1, both microalgae maintained good photosynthetic and physiological activity, with a maximum quantum yield potential ranging from 0.6 to 0.7. At the phenol concentration of 300 mg L-1, the biomass of C. pyrenoidosa was 2.4 times that of the control group. For S. obliquus, at the phenol concentration of 150 mg L-1, the biomass was approximately 0.85 g L-1, which increased by 68% than that of the control group (0.58 g L-1). The lipid content in both microalgae increased with the phenol concentrations, with the maximum content exceeding 40%. The optimal phenol concentrations for C. pyrenoidosa and S. obliquus growth were determined to be 246.18 and 152.73 mg L-1, respectively, based on a developed kinetic model. This work contributes to further elucidating the effects of phenol on microalgae growth, photosynthesis, and intracellular components, and suggests that using microalgae to treat phenol-containing coking wastewater for producing biofuel is not only environmentally friendly but also holds significant energy promise.

Extraction and characterization of nanocellulose from cattail leaves: Morphological, microstructural and thermal properties.

Hydrogen peroxide combined with acid treatment demonstrates its respective characteristics for the separation of lignocellulosic biomass. Herein, holocellulose was extracted from Cattail leaves (CL) by a two-step treatment with alkali and hydrogen peroxide-acetic acid (HPAA). Then carboxylated nanocellulose was hydrolyzed with a mixed organic/inorganic acid. The chemical composition of the holocellulose and the physicochemical properties of the separated carboxylated nanocellulose were comparable. Carboxyl groups were introduced on the nanocellulose as a result of the esterification process with citric acid (CA), which endows the nanocellulose with high thermal stability (315-318 °C) and good light transmission (>80 %). Furthermore, morphological analyses revealed that nanocellulose had a spider-web-like structure with diameter between 5 and 20 nm.

Hierarchical Flower-like Sulfides with Increased Entropy for Electromagnetic Wave Absorption.

The concept of high entropy is considered promising to enhance electromagnetic wave absorption properties. However, preparing high-entropy sulfides with unique structures for high-performance electromagnetic absorption remains a challenge. In this study, hierarchical porous flower-like dual-phase sulfides were designed with increased entropy and fabricated using a versatile approach. The porous flower configuration enhanced the scattering of electromagnetic waves and the impedance-matching characteristics. Additionally, the effect of high entropy induced diverse defects that were favorable for electromagnetic wave dissipation in dual-phase sulfides. The design of the dual-phase structure generated strong interface polarization, and the composition and content of the phases exhibited clear changes with the increase in the number of metal elements. Interestingly, apparent lattice distortions, defects, and shear strains were directly observed near the dual-phase interface of millerite (102) and pyrite (220) planes, facilitating the occurrence of dipole polarization. Consequently, the developed dual-phase high-entropy sulfide exhibited outstanding microwave absorption properties. The minimum reflection loss value of (FeCoNiCuZn)S was -45.8 dB at a thickness of 1.5 mm, and the optimal effective absorption bandwidth was 3.8 GHz at a thickness of 1.4 mm thickness. Thus, the design of high-entropy sulfides brings meaningful guidance for tuning the wave absorption properties in sulfides.

Lymphadenectomy and optimal excise lymph nodes count for early-stage primary fallopian tube cancer: a SEER-based study.

BACKGROUNDS: There is still no consensus on the significance of Lymphadenectomy (LD) and the number of lymph nodes that need to be excised (ELNs) for adequate LD in patients with early-stage primary fallopian tube cancer (PFTC). Our endeavor is geared towards deepening comprehension of LD in early-stage PFTC and identify the optimal cut-off of ELNs. METHODS: This SEER-based study analyzed the clinical data of patients with early-stage PFTC between 2000 and 2018. X-tile was employed to confirm the optimal cut-off of ELNs. The survival data between groups were analyzed by the Kaplan-Meier estimates, Log-rank test and Cox proportional hazards model. RESULTS: There was significant improvement in both mean cancer-specific survival (CSS, p < 0.001) and overall survival (OS, p < 0.001) in LD group. Regardless of matched or not, LD was identified as an independent protective factor of CSS and OS. The optimal 3-year CSS-based cutoff of ELNs was 11 (p = 0.026) as determined by X-tile. Both the mean CSS (p = 0.001) and mean OS (p = 0.002) in adequate LD group (ELNs > 11, n = 574) were significantly longer than these in inadequate LD group (ELNs ≤ 11, n = 738). Adequate LD, FIGO stage, tumor grade and histology were significant prognostic factors for CSS and OS. CONCLUSION: LD is an independent protective prognostic factor of patients with early-stage PFTC. The association between ELNs > 11 and an improved prognosis is evident. Future studies are needed to further clarify the results above.

Bromodomain and extraterminal (BET) proteins: biological functions, diseases, and targeted therapy.

BET proteins, which influence gene expression and contribute to the development of cancer, are epigenetic interpreters. Thus, BET inhibitors represent a novel form of epigenetic anticancer treatment. Although preliminary clinical trials have shown the anticancer potential of BET inhibitors, it appears that these drugs have limited effectiveness when used alone. Therefore, given the limited monotherapeutic activity of BET inhibitors, their use in combination with other drugs warrants attention, including the meaningful variations in pharmacodynamic activity among chosen drug combinations. In this paper, we review the function of BET proteins, the preclinical justification for BET protein targeting in cancer, recent advances in small-molecule BET inhibitors, and preliminary clinical trial findings. We elucidate BET inhibitor resistance mechanisms, shed light on the associated adverse events, investigate the potential of combining these inhibitors with diverse therapeutic agents, present a comprehensive compilation of synergistic treatments involving BET inhibitors, and provide an outlook on their future prospects as potent antitumor agents. We conclude by suggesting that combining BET inhibitors with other anticancer drugs and innovative next-generation agents holds great potential for advancing the effective targeting of BET proteins as a promising anticancer strategy.

Self-assembly of three-dimensional liver organoids: virtual reconstruction via endocytosed polymer dots for refactoring the fine structure.

In vitro culture of organoids holds considerable promise for the treatment of diseases or the provision of artificial organs. Traditional 2D differentiation from mesenchymal stem cells (MSCs) faces challenges in replicating the development of embryonic organs at the cellular level; conversely, the cultivation of 3D organoids exhibits potential for application. It is crucial for clinicians and technology researchers to acquire insights into organoid tissue differentiation, autonomous morphogenesis, as well as 3D assembly processes in vitro. In this investigation, novel 3D organoids capable of engendering complex liver-like tissues in vitro were cultured, and a class of high-luminance semiconductor polymer dots (Pdots) was employed to monitor the self-assembly process of 3D liver organoid tissues and cellular interaction and migration dynamics. Three-dimensional liver-bud (3D-LB) organoid tissues were derived through the interplay of induced MSCs, Wharton's Jelly, and human umbilical vein endothelial cells (HUVECs), and their structural characteristics were determined during the liver-bud organoid development; ultimately, the co-cultured organoid spatial cellular clusters resembling a truffle were successfully replicated. Utilizing R8-Pdots with remarkable resolution and biocompatibility, the structural elements of functional and vascularized organs derived from liver organoid tissues were adeptly reconstituted, and this investigation shall contribute to a further understanding of human hepato-developmental physiology and liver-disease modeling.

HimGNN: a novel hierarchical molecular graph representation learning framework for property prediction.

Accurate prediction of molecular properties is an important topic in drug discovery. Recent works have developed various representation schemes for molecular structures to capture different chemical information in molecules. The atom and motif can be viewed as hierarchical molecular structures that are widely used for learning molecular representations to predict chemical properties. Previous works have attempted to exploit both atom and motif to address the problem of information loss in single representation learning for various tasks. To further fuse such hierarchical information, the correspondence between learned chemical features from different molecular structures should be considered. Herein, we propose a novel framework for molecular property prediction, called hierarchical molecular graph neural networks (HimGNN). HimGNN learns hierarchical topology representations by applying graph neural networks on atom- and motif-based graphs. In order to boost the representational power of the motif feature, we design a Transformer-based local augmentation module to enrich motif features by introducing heterogeneous atom information in motif representation learning. Besides, we focus on the molecular hierarchical relationship and propose a simple yet effective rescaling module, called contextual self-rescaling, that adaptively recalibrates molecular representations by explicitly modelling interdependencies between atom and motif features. Extensive computational experiments demonstrate that HimGNN can achieve promising performances over state-of-the-art baselines on both classification and regression tasks in molecular property prediction.