Signaling Complex Research Articles

Cosmetic retinoid use in photoaged skin: A review of the compounds, their use and mechanisms of action.

The inevitable attrition of skin due to ultraviolet radiation, termed photoaging, can be partially restored by treatment with retinoid compounds. Photoaged skin in lightly pigmented individuals, clinically presents with the appearance of wrinkles, increased laxity, and hyper- and hypopigmentation. Underlying these visible signs of ageing are histological features such as epidermal thinning, dermal-epidermal junction flattening, solar elastosis and loss of the dermal fibrillin microfibrillar network, fibrillar collagen and glycosaminoglycans. Retinoid compounds are comprised of three main generations with the first generation (all-trans retinoic acid, retinol, retinaldehyde and retinyl esters) primarily used for the clinical and cosmetic treatment of photoaging, with varying degrees of efficacy, tolerance and stability. All-trans retinoic acid is considered the 'gold standard' for skin rejuvenation; however, it is a prescription-only product largely confined to clinical use. Therefore, retinoid derivatives are readily incorporated into cosmeceutical formulations. The literature reported in this review suggests that retinol, retinyl esters and retinaldehyde that are used in many cosmeceutical products, are efficacious, safe and well-tolerated. Once in the skin, retinoids utilize a complex signalling pathway that promotes remodelling of photoaged epidermis and dermis and leads to the improvement of the cutaneous signs of photoaging.

HIF-1α protects nucleus pulposus cells from oxidative stress-induced mitochondrial impairment through PDK-1

The pathogenesis of intervertebral disc degeneration (IVDD) involves complex signaling networks and various effector molecules, and our understanding of the pathogenesis of IVDD is limited. Hypoxia inducible factor-1α (HIF-1α) is closely related to IVDD, and there is excessive oxidative stress concurrent with IVDD. In this study, we found that HIF-1α could protect nucleus pulposus cells from excessive oxidative stress by reversing the imbalance between oxidants and antioxidants and thus mitigating the oxidative stress-induced mitochondrial impairment. With further exploration, we found that pyruvate dehydrogenase kinase 1 (PDK-1) was involved in the protective effect of HIF-1α on nucleus pulposus cells under oxidative stress. We suggested that HIF-1α could preserve the mitochondrial integrity and activate glycolysis in nucleus pulposus cells via PDK-1, and the addition of DCA, a PDK-1 inhibitor, could blunt the protective effect of HIF-1α. In addition, the HIF-1α/PDK-1 regulatory axis was also confirmed in vivo through HIF-1α knockout mice model. Therefore, we propose that HIF-1α protects nucleus pulposus cells from excessive oxidative stress by maintaining the mitochondrial integrity and glycolysis via PDK-1, thus enriching the insight into the protective mechanism of HIF-1α against IVDD, and providing a novel therapeutic target for the treatment of IVDD.

Control of Dopamine Signal in High-Order Receptor Complex on Striatal Astrocytes.

The receptor-receptor interaction (RRI) of G protein-coupled receptors (GPCRs) leads to new functional entities that are conceptually distinct from the simple addition of signals mediated by the activation of the receptors that form the heteromers. Focusing on astrocytes, there is evidence for the existence of inhibitory and facilitatory RRIs, including the heteromers formed by the adenosine A2A and the dopamine D2 receptors, by A2A and the oxytocin receptor (OTR), and the D2-OTR heteromers. The possible involvement of these receptors in mosaicism has never been investigated in striatal astrocytes. By biophysical and functional approaches, we focused our attention on the existence of an A2A-D2-OTR high-order receptor complex and its role in modulating cytosolic calcium levels and endogenous glutamate release, when striatal astrocyte processes were stimulated with 4-aminopyridine. Functional data indicate a permissive role of OTR on dopamine signaling in the regulation of the glutamatergic transmission, and an inhibitory control mediated by A2A on both the D2-mediated signaling and on the OTR-facilitating effect on D2. Imaging biochemical and bioinformatic evidence confirmed the existence of the A2A-D2-OTR complex and its ternary structure in the membrane. In conclusion, the D2 receptor appears to be a hotspot in the control of the glutamate release from the astrocytic processes and may contribute to the regulation and integration of different neurotransmitter-mediated signaling in the striatum by the A2A-D2-OTR heterotrimers. Considering the possible selectivity of allosteric interventions on GPCRs organized as receptor mosaics, A2A-D2-OTR heterotrimers may offer selective pharmacological targets in neuropsychiatric disorders and neurodegenerative diseases.

Focal Adhesion Maturation Responsible for Behavioral Changes in Human Corneal Stromal Fibroblasts on Fibrillar Substrates.

The functioning of the human cornea heavily relies on the maintenance of its extracellular matrix (ECM) mechanical properties. Within this context, corneal stromal fibroblasts (CSFs) are essential, as they are responsible for remodeling the corneal ECM. In this study, we used a decellularized human amniotic membrane (dHAM) and a custom fibrillar collagen film (FCF) to explore the effects of fibrillar materials on human CSFs. Our findings indicate that substrates like FCF can enhance the early development of focal adhesions (FAs), leading to the activation and propagation of mechanotransduction signals. This is primarily achieved through FAK autophosphorylation and YAP1 nuclear translocation pathways. Remarkably, inhibiting FAK autophosphorylation negated the observed changes. Proteome analysis further confirmed the central role of FAs in mechanotransduction propagation in CSFs cultured on FCF. This analysis also highlighted complex signaling pathways, including chromatin epigenetic modifications, in response to fibrillar substrates. Overall, our research highlights the potential pathways through which CSFs undergo behavioral changes when exposed to fibrillar substrates, identifying FAs as essential mechanotransducers.

Response of the emerald‐spotted wood‐dove to the song of conspecific males and sympatric congeners

AbstractBird song contains crucial information that enables recognition of conspecific individuals from a distance, which facilitates subsequent complex behaviors related to mate attraction and rival deterrence. Loud broadcast signals of non‐learning bird species are usually treated as less complex than songs of Oscines, but several studies have revealed that song learning is not necessary for the evolution of complex signaling. Here, we focused on a species of African wood‐dove which produces superficially simple songs consisting of short notes organized into two parts of different amplitude. Our model was a population of emerald‐spotted wood‐doves (Turtur chalcospilos) that live in the same area as the physically and vocally similar blue‐spotted wood‐dove (Turtur afer). We tested the responses of male emerald‐spotted wood‐doves to different playbacks simulating territorial intrusion. We used songs of the focal species and of the congener, two types of artificially mixed songs with different parts belonging to the focal or congeneric species, and a control song. We aimed to assess (i) whether the focal species responds only to its own species' song or exhibits interspecific territoriality, and (ii) which part of the song is responsible for coding species identity. We found that male emerald‐spotted wood‐doves responded strongly to playback, but almost exclusively approached only the playback of their own species' song. Additionally, only conspecific song caused a decrease in song rate during playback and an increase in song output after playback. Our results suggest that emerald‐spotted wood‐doves are able to discriminate their own songs from those of congeners and do not exhibit interspecies territoriality. We were unable to identify a single part of the song that codes species‐specificity, as mixed songs of any kind did not substantially increase responsiveness to playback in comparison to the congener song or the control. We discuss these results in the context of current hypotheses regarding interspecific territoriality and the evolution of species‐identity coding.

Hybrid vibration isolator based on piezoelectric actuator and metal rubber and its adaptive control method

To achieve vibration isolation across the entire working frequency range, this paper proposes a novel hybrid vibration isolator combining metal rubber and piezoelectric actuators, along with an adaptive active control algorithm. The passive isolation system allows for manual adjustment of stiffness and damping based on the preload, overcoming the issue of fixed stiffness and damping in traditional passive isolation units. For the active isolation system, an improved Filtered-x Normalized Least Mean Squares with adaptive step size active control algorithm is proposed, overcoming the problem of narrow frequency range applicability in traditional active control algorithms. A hybrid model of electromechanical coupling and hysteresis for the piezoelectric actuator is developed for the secondary path in the algorithm. Experimental results confirm that the hybrid isolator possesses vibration isolation capabilities within the 5–500 Hz working frequency range, with vibration suppression at the first and second resonance frequencies improved by 98.9% and 92.2%, respectively, compared to the passive system. Additionally, the hybrid isolator effectively suppresses complex multifrequency signals and demonstrates robustness and adaptability. This research provides advanced technological means to address complex vibration problems, and establishes both theoretical and practical foundations for multi-degree-of-freedom vibration isolation.

An intracellular phosphorus-starvation signal activates the PhoB/PhoR two-component system in Salmonella enterica.

Bacteria acquire P primarily as inorganic orthophosphate (Pi, PO43-). Once internalized, Pi is rapidly assimilated into biomass during the synthesis of ATP. Because Pi is essential, but excessive ATP is toxic, the acquisition of environmental Pi is tightly regulated. In the bacterium Salmonella enterica (Salmonella), growth in Pi-limiting environments activates the membrane sensor histidine kinase PhoR, leading to the phosphorylation of its cognate transcriptional regulator PhoB and subsequent transcription of genes involved in adaptations to low Pi. Pi limitation promotes PhoR kinase activity by altering the conformation of a membrane signaling complex comprised of PhoR, the multicomponent Pi transporter system PstSACB and the regulatory protein PhoU. However, the identity of the Pi-starvation signal and how it controls PhoR activity remain unknown. Here, we identify conditions where the PhoB and PhoR signal transduction proteins can be maintained in an inactive state when Salmonella is grown in media lacking Pi. Our results demonstrate that PhoB/PhoR is activated by an intracellular P-insufficiency signal.IMPORTANCEIn enteric bacteria, the transcriptional response to phosphorus (P) starvation is controlled by a specialized signal transduction system comprised of a membrane-bound, multicomponent signal sensor, and a cytoplasmic transcriptional factor. Whereas this system has been primarily studied in the context of phosphate (Pi) starvation, it is currently unknown how this stress initiates signal transduction. In the current study, we establish that this signaling system is regulated by a cytoplasmic signal arising from insufficient P. We demonstrate that rather than responding to extracellular conditions, cells couple the activation of their P starvation response to the availability of cytoplasmic P. This regulatory logic may enable cells to prevent toxicity resulting from excessive Pi acquisition and hinder the onset of a P starvation response when their metabolic demands are being met through the consumption of P sources other than Pi.

MosGraphGPT: a foundation model for multi-omic signaling graphs using generative AI.

Generative pretrained models represent a significant advancement in natural language processing and computer vision, which can generate coherent and contextually relevant content based on the pre-training on large general datasets and fine-tune for specific tasks. Building foundation models using large scale omic data is promising to decode and understand the complex signaling language patterns within cells. Different from existing foundation models of omic data, we build a foundation model, mosGraphGPT, for multi-omic signaling (mos) graphs, in which the multi-omic data was integrated and interpreted using a multi-level signaling graph. The model was pretrained using multi-omic data of cancers in The Cancer Genome Atlas (TCGA), and fine-turned for multi-omic data of Alzheimer's Disease (AD). The experimental evaluation results showed that the model can not only improve the disease classification accuracy, but also is interpretable by uncovering disease targets and signaling interactions. And the model code are uploaded via GitHub with link: https://github.com/mosGraph/mosGraphGPT.

Fractional synchrosqueezing transform for enhanced multicomponent signal separation

The precise separation of multicomponent signals encounters numerous challenges due to the complexity of signals and widespread interference. Synchrosqueezing Transform (SST) is one of the important technologies for improving the accurate separation of multicomponent signals, but it faces challenges in terms of the difficulty and effectiveness of squeezing. This paper introduces a multicomponent signal separation method based on innovative Fractional Synchrosqueezing Transform (FrSST). FrSST rearranges along the fractional frequency axis, improving the accuracy of time–frequency ridges and, consequently, enhancing the precision of multicomponent signal separation. In the signal reconstruction process, chirp multiplication and energy rearrangement compensate for chirp bases’ effects, boosting energy concentration and reconstruction potential. Utilizing improved ridges from FrSST ensures effective signal reconstruction. Simulation comparisons demonstrate that, with varying SNRs from − 5 to 15 dB, the reconstructed components based on FrSST exhibit favorable approximation to the original signal components. Furthermore, as the sample size increases, the proposed algorithm shows satisfactory computational efficiency.

Multiple mechanisms contribute to acquired TRAIL resistance in multiple myeloma

Multiple Myeloma (MM) prognosis has recently improved thanks to the incorporation of new therapies to the clinic. Nonetheless, it is still a non-curable malignancy. Targeting cancer cells with agents inducing cell death has been an appealing alternative investigated over the years, as is the case of TRAIL, an agonist of DR4 and DR5 death receptors. This pathway, involved in apoptosis triggering, has demonstrated efficacy on MM cells. In this research, we have investigated the sensitivity of a panel of MM cells to this agent and generated TRAIL-resistant models by continuous culture of sensitive cells with this peptide. Using genomic and biochemical approaches, the mechanisms underlying resistance were investigated. In TRAIL-resistant cells, a strong reduction in cell-surface receptor levels was detected and impaired the apoptotic machinery to respond to the treatment, enabling cells to efficiently form the Death Inducing Signalling Complex. In addition, an upregulation of the inhibitory protein c-FLIP was detected. Even though the manipulation of these proteins was able to modify cellular responses to TRAIL, it was not complete, pointing to other mechanisms involved in TRAIL resistance.

Triboelectric Nanogenerators with Machine Learning for Internet of Things

AbstractThe development of the Internet of Things (IoT) indicates that humankind has entered a new intelligent era of the “Internet of Everything”. Thanks to the characteristics of low‐cost, diverse structure, and high energy conversion efficiency, the self‐powered sensing systems, which are based on the Triboelectric Nanogenerator (TENG), demonstrate great potential in the field of IoT. In order to solve the challenges of TENG in sensing signal processing, such as signal noise and nonlinear relations, Machine Learning (ML), which is an efficient and mature data processing tool, is widely applied for efficiently processing the large and complex output signal data generated by TENG intelligent sensing system. This review summarizes and analyzes the adaptation of different algorithms in TENG and their advantages and disadvantages at the beginning, which provides a reference for the selection of algorithms for TENG. More importantly, the application of TENG is introduced in multiple scenarios, including health monitoring, fault detection, and human‐computer interaction. Finally, the limitations and development trend of the integration of TENG and ML are proposed by classification to promote the future development of the intelligent IoT era.

Abstract We133: In Silico Model of Cardiomyopathy Caused by a MYBPC3-induced HCM Mutation

Introduction: Hypertrophic cardiomyopathy (HCM) is the most frequent hereditary cardiomyopathy and a leading cause of sudden cardiac death, particularly in adolescent. Despite recent improved prognosis and FDA approved drugs, current cardiac therapeutics cannot efficiently prevent remodeling across all HCM patient populations due to genetic variability. Therefore, we require a systems biology approach to understand how the complex cardiac signaling networks regulate cardiomyocyte shape and size due to an HCM mutation. This study leverages a computational systems approach to explore MYBPC3-induced HCM mutation regulation of cardiomyocyte hypertrophy. Method: For the signaling network model, we employed a logic-based differential equations model (NETFLUX) to construct a signaling network validated using in vitro data from published studies. This model captured signaling dynamics and cross talks between pathways governing cardiomyocyte size and shape. Additionally, a MYBPC3 HCM mutation is integrated in the model as an input providing a comparison between a control and simulated HCM responses. Sensitivity analyses are performed to investigate the most influential signaling pathways that mediate changes in mass. Results: We created a MYBPC3-induced HCM model by integrating an additional cardiac myosin binding protein-C node to a previously validated inherited cardiomyopathy signaling network. This updated model predicted an increase in mass when the HCM mutation is simulated. The simulated inhibition of each node in the model revealed that inhibition of calcium pathway, growth factor receptor, and titin stiffness could mitigate the HCM phenotype by reducing mass. The sensitivity analysis results also suggested PI3K, Ras, and ERK1/2 pathways as potential mechanisms mediating the decrease in mass and served as potential therapeutic targets. Discussion and Future Work: Our systems approach gave insights on the mechanisms governing the cardiomyocyte response to a MYBPC3-induced HCM mutation. This will be further validated via a MYBPC3-HCM model using human iPSC-CMs with MYBPC3-induced mutations. This will create a cell line that will provide genetically precise comparisons for identifying new molecular mechanisms of disease, thereby offering a strategy for advancing precision medicine.

Histopathological analysis potential for unveiling hormone signaling in endocrine-related tumors.

Elucidating the mechanisms of action of steroid hormones will contribute to the development of therapeutic strategies for hormone-dependent tumors. Recent advances in genetic engineering have revealed the complex and diverse mechanisms of steroid hormone signaling; however, these techniques are limited to in vitro or animal experiments. It is believed that verifying hormone signals elucidated using human pathological tissue specimens will directly aid in treatment and diagnosis. However, pathological tissue specimens are generally formalin-fixed paraffin-embedded (FFPE), and protein/gene analyses of FFPE tissues are limited. Protein detection using immunohistochemistry with specific antibodies in FFPE tissues is a classical technique essential for diagnosis and treatment decisions in various types of cancer. In steroid hormone signaling, the expression and localization of receptors, hormone-related enzymes, and proteins encoded by response genes can be clarified using immunohistochemistry. Although protein-protein interactions such as receptor dimers and DNA-binding proteins are mainly detected in vitro, they can be examined in FFPE tissues using in situ proximity ligation assays and southwestern histochemistry, respectively. Using these detection methods, including immunohistochemistry, it is possible to analyze each hormone signaling pathway in hormone-related tumors histopathologically. Although FFPE tissues still suffer from gene and protein denaturation, their advantages include the ability to retrospectively study target factors/signals and obtain spatial information through microscopy. This review describes a visualization method for elucidating steroid hormone signaling in hormone-dependent tumors using FFPE tissues.

An automatic recognition method for power quality disturbances based on CAB-Net

Abstract The accurate identification of power quality disturbances (PQDs) is crucial for maintaining the stability and reliability of power systems. In this paper, an automatic identification method for PQDs based on CNN-BiGRU-Attention Network (CAB-Net) is proposed. To handle the temporal characteristics and complexity of composite PQDs signals, the proposed model leverages the bidirectional information transmission of the BiGRU model to efficiently extract temporal features. Furthermore, to boost recognition accuracy, an attention mechanism is incorporated, the key information can be intelligently locked in the feature extraction stage, and the information can be efficiently screened and utilized, thereby enhancing its ability to identify power quality disturbance signals. To confirm the validity of the method, we use the simulation data for experimental proof. Experimental results demonstrate that compared to traditional power quality disturbance identification methods, the method has excellent recognition ability and stronger robustness.

Reviewing mathematical models of sperm signaling networks.

Dave Garbers' work significantly contributed to our understanding of sperm's regulated motility, capacitation, and the acrosome reaction. These key sperm functions involve complex multistep signaling pathways engaging numerous finely orchestrated elements. Despite significant progress, many parameters and interactions among these elements remain elusive. Mathematical modeling emerges as a potent tool to study sperm physiology, providing a framework to integrate experimental results and capture functional dynamics considering biochemical, biophysical, and cellular elements. Depending on research objectives, different modeling strategies, broadly categorized into continuous and discrete approaches, reveal valuable insights into cell function. These models allow the exploration of hypotheses regarding molecules, conditions, and pathways, whenever they become challenging to evaluate experimentally. This review presents an overview of current theoretical and experimental efforts to understand sperm motility regulation, capacitation, and the acrosome reaction. We discuss the strengths and weaknesses of different modeling strategies and highlight key findings and unresolved questions. Notable discoveries include the importance of specific ion channels, the role of intracellular molecular heterogeneity in capacitation and the acrosome reaction, and the impact of pH changes on acrosomal exocytosis. Ultimately, this review underscores the crucial importance of mathematical frameworks in advancing our understanding of sperm physiology and guiding future experimental investigations.

Structure and assembly of the human IL-12 signaling complex

Interleukin (IL)-12 is a heterodimeric pro-inflammatory cytokine. Our cryoelectron microscopy structure determination of human IL-12 in complex with IL-12Rβ1 and IL-12Rβ2 at a resolution of 3.75Å reveals that IL-12Rβ2 primarily interacts with the IL-12p35 subunit via its N-terminal Ig-like domain, while IL-12Rβ1 binds to the p40 subunit with its N-terminal fibronectin III domain. This binding mode of IL-12 with its receptors is similar to that of IL-23 but shows notable differences with other cytokines. Through structural information and biochemical assays, we identified Y62, Y189, and K192 as key residues in IL-12p35, which bind to IL-12Rβ2 with high affinity and mediate IL-12 signal transduction. Furthermore, structural comparisons reveal two distinctive conformational states and structural plasticity of the heterodimeric interface in IL-12. As a result, our study advances our understanding of IL-12 signal initiation and opens up new opportunities for the engineering and therapeutic targeting of IL-12.

FAK Family Kinases: A Potential Therapeutic Target for Atherosclerosis.

Atherosclerosis (AS) is a chronic progressive inflammatory disease of the vascular wall and the primary pathological basis of cardiovascular and cerebrovascular disease. Focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (Pyk2), two highly homologous members of the FAK family kinases, play critical roles in integrin signaling. They also serve as scaffolding proteins that contribute to the assembly of cellular signaling complexes that regulate cell survival, cell cycle progression, and cell motility. Research indicates that the FAK family kinases is involved in the gene regulation of vascular cells and that aberrant expression of this family is associated with pathological changes in vascular disease. These findings establish the FAK family kinases as a critical signaling mediator in atherosclerotic lesions and inhibition of its activity has the potential to attenuate the pathological progression of AS. This review highlights the indispensable role of the FAK family kinases in abnormal vascular smooth muscle cell proliferation, endothelial cell dysfunction, inflammation, and lipid metabolism associated with AS. We also summarize therapeutic targets against the FAK family kinases, providing valuable insights into therapeutic strategies for AS.

Acute effects of whole-body vibration on unilateral isometric knee extensors maximal torque and fatigability during an intermittent endurance task in adult males

Whole-body vibration (WBV) has been employed for performance-enhancing purposes. WBV may positively affect muscular endurance and its underlying neural mechanisms due to an enhanced muscular blood circulation and oxygen uptake. However, the effects of WBV on endurance-related torque signal complexity have been understudied. This study aims to investigate the acute effects of WBV on i) maximal isometric torque production; ii) isometric knee extensors fatigability and iii) torque signal complexity during an isometric endurance task.Thirty adult males performed an isometric intermittent endurance protocol on their dominant lower limb after performing: static half squat with WBV (WBV), static half squat without WBV (HS), and no exercise protocol (CC). For each repetition the maximal torque was identified. The maximal torque of the first repetition was identified as the PeakT. The Mean torque (MTorque) and fatigue index (pFatigue) were calculated as the mean and the percentage decay in torque across the entire set of eighteen repetitions (MTorque0–100 %, pFatigue0–100 %), and across shorter blocks of six repetitions (MTorque0–33 %, pFatigue0–33 %; MTorque34–66 %, pFatigue34–66 %, and MTorque67–100 %, pFatigue67–100 %). Torque fluctuations were analysed computing Sample Entropy (SampEn) and the coefficient of variation (CV).PeakT was significantly higher in CC than in WBV (p < 0.01) and in HS (p < 0.01). PeakT was significantly higher in HS than in WB (p < 0.05). MTorque0–100 %, MTorque0–33 %, MTorque34–66 %, and MTorque67–100 % were significantly higher in CC than in WBV (all p-values <0.01) and in HS (p < 0.01). MTorque67–100 % was significantly higher in HS than in WB (p = 0.049). pFatigue34–66 % was significantly higher in WBV than in CC (p < 0.05) whereas pFatigue67–100 % was significantly higher in CC than in WB (p < 0.01) and in HS (p < 0.01). No effect of condition was observed for SampEn and CV.Acute WBV does not lead to beneficial effects on maximal torque production and isometric knee extensors fatigability. These acute detrimental effects may be related to long-term WBV-related adaptations.

Actin network evolution as a key driver of eukaryotic diversification.

Eukaryotic cells have been evolving for billions of years, giving rise to wildly diverse cell forms and functions. Despite their variability, all eukaryotic cells share key hallmarks, including membrane-bound organelles, heavily regulated cytoskeletal networks and complex signaling cascades. Because the actin cytoskeleton interfaces with each of these features, understanding how it evolved and diversified across eukaryotic phyla is essential to understanding the evolution and diversification of eukaryotic cells themselves. Here, we discuss what we know about the origin and diversity of actin networks in terms of their compositions, structures and regulation, and how actin evolution contributes to the diversity of eukaryotic form and function.

Research advances on signaling pathways regulating the polarization of tumor-associated macrophages in lung cancer microenvironment.

Lung cancer (LC) is one of the most common cancer worldwide. Tumor-associated macrophages (TAMs) are important component of the tumor microenvironment (TME) and are closely related to the stages of tumor occurrence, development, and metastasis. Macrophages are plastic and can differentiate into different phenotypes and functions under the influence of different signaling pathways in TME. The classically activated (M1-like) and alternatively activated (M2-like) represent the two polarization states of macrophages. M1 macrophages exhibit anti-tumor functions, while M2 macrophages are considered to support tumor cell survival and metastasis. Macrophage polarization involves complex signaling pathways, and blocking or regulating these signaling pathways to enhance macrophages' anti-tumor effects has become a research hotspot in recent years. At the same time, there have been new discoveries regarding the modulation of TAMs towards an anti-tumor phenotype by synthetic and natural drug components. Nanotechnology can better achieve combination therapy and targeted delivery of drugs, maximizing the efficacy of the drugs while minimizing side effects. Up to now, nanomedicines targeting the delivery of various active substances for reprogramming TAMs have made significant progress. In this review, we primarily provided a comprehensive overview of the signaling crosstalk between TAMs and various cells in the LC microenvironment. Additionally, the latest advancements in novel drugs and nano-based drug delivery systems (NDDSs) that target macrophages were also reviewed. Finally, we discussed the prospects of macrophages as therapeutic targets and the barriers to clinical translation.