Effects of biodegradable microplastics and straw addition on soil greenhouse gas emissions.

Large pieces of plastic are transformed into microplastic particles through weathering, abrasion, and ultraviolet radiation, significantly impacting the soil ecosystem. However, studies on biodegradable microplastics replacing traditional microplastics as agricultural mulching films to drive the biogeochemical processes influenced by GHG are still in their initial stages, with limited relevant reports available. This study sought to investigate the effects of microplastic and straw addition on CO2 and N2O emissions in different soils. Herein, yellow-brown soil (S1) and fluvo-aquic soil (S2) were utilized, each treated with three different concentrations of PLA (polylactic acid) microplastics (0.25%, 2%, and 7% w/w) at 25 °C for 35 days, with and without straw addition. The results showed that straw (1% w/w) significantly increased soil CO2 by 4.1-fold and 3.2-fold, respectively, and N2O by 1.8-fold and 1.8-fold, respectively, in cumulative emissions in S1 and S2 compared with the control. PLA microplastics significantly increased CO2 emissions by 71.5% and 99.0% and decreased N2O emissions by 30.1% and 24.7% at a high concentration (7% w/w, PLA3) in S1 and S2 compared with the control, respectively. The same trend was observed with the addition of straw and microplastics together. Structural equation modeling and redundancy analysis confirmed that soil physiochemical parameters, enzyme and microbial activities are key factors regulating CO2 and N2O emissions. The addition of microplastics is equivalent to the addition of carbon sources, which can significantly affect DOC, MBC, SOC and the abundance of carbon-associated bacteria (CbbL), thereby increasing soil CO2 emissions. The addition of microplastics alone inhibited the activity of nitrogen cycling enzymes (urease activity), increasing the abundance of denitrifying microbes. However, adding a high amount of microplastics and straw together released plastic additives, inhibiting microbial abundance and reducing the nitrogen cycle. These effects decreased NH4+-N and increased NO3--N, resulting in decreased N2O emissions. This study indicates that biodegradable microplastics could reduce soil plastic residue pollution through degradation. However, their use could also increase CO2 emissions and decrease N2O emissions. Consequently, this research lays the groundwork for further investigation into the implications of utilizing biodegradable microplastics as agricultural mulch, particularly concerning soil geochemistry and GHG emissions.

The Neurocomputational Mechanism Underlying Decision-Making on Unfairness to Self and Others.

Fairness is a fundamental value in human societies, with individuals concerned about unfairness both to themselves and to others. Nevertheless, an enduring debate focuses on whether self-unfairness and other-unfairness elicit shared or distinct neuropsychological processes. To address this, we combined a three-person ultimatum game with computational modeling and advanced neuroimaging analysis techniques to unravel the behavioral, cognitive, and neural patterns underlying unfairness to self and others. Our behavioral and computational results reveal a heightened concern among participants for self-unfairness over other-unfairness. Moreover, self-unfairness consistently activates brain regions such as the anterior insula, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex, spanning various spatial scales that encompass univariate activation, local multivariate patterns, and whole-brain multivariate patterns. These regions are well-established in their association with emotional and cognitive processes relevant to fairness-based decision-making. Conversely, other-unfairness primarily engages the middle occipital gyrus. Collectively, our findings robustly support distinct neurocomputational signatures between self-unfairness and other-unfairness.

Host specificity of plant-associated bacteria is negatively associated with genome size and host abundance along a latitudinal gradient.

Host specialization plays a critical role in the ecology and evolution of plant-microbe symbiosis. Theory predicts that host specialization is associated with microbial genome streamlining and is influenced by the abundance of host species, both of which can vary across latitudes, leading to a latitudinal gradient in host specificity. Here, we quantified the host specificity and composition of plant-bacteria symbioses on leaves across 329 tree species spanning a latitudinal gradient. Our analysis revealed a predominance of host-specialized leaf bacteria. The degree of host specificity was negatively correlated with bacterial genome size and the local abundance of host plants. Additionally, we found an increased host specificity at lower latitudes, aligning with the high prevalence of small bacterial genomes and rare host species in the tropics. These findings underscore the importance of genome streamlining and host abundance in the evolution of host specificity in plant-associated bacteria along the latitudinal gradient.

Enzyme-mediated green synthesis of glycosaminoglycans and catalytic process intensification.

Glycosaminoglycans (GAGs) are a family of structurally complex heteropolysaccharides that play pivotal roles in biological functions, including the regulation of cell proliferation, enzyme inhibition, and activation of growth factor receptors. Therefore, the synthesis of GAGs is a hot research topic in drug development. The enzymatic synthesis of GAGs has received widespread attention due to their eco-friendly nature, high regioselectivity, and stereoselectivity. The enhancement of the enzymatic synthesis process is the key to its industrial applications. In this review, we overviewed the construction of more efficient in vitro biomimetic synthesis systems of glycosaminoglycans and presented the different strategies to improve enzyme catalysis, including the combination of chemical and enzymatic methods, solid-phase synthesis, and protein engineering to solve the problems of enzyme stability, separation and purification of the product, preparation of structurally defined sugar chains, etc., and discussed the challenges and opportunities in large-scale green synthesis of GAGs.

Aged microbiota exacerbates cardiac failure by PPARα/PGC1α pathway.

The dysbiosis of gut microbiota with aging has been extensively studied, revealing its substantial contribution to variety of diseases. However, the impact of aged microbiota in heart failure (HF) remains unclear. In this study, we employed the method of fecal microbiota transplantation (FMT) from aged donors to investigate its role in the context of HF. Our results demonstrate that FMT from aged donors alters the recipient's gut microbiota composition and abundance. Furthermore, FMT impairs cardiac function and physical activity in HF mice. Aged FMT induces metabolic alterations, leading to body weight gain, impaired glucose tolerance, increased respiratory exchange ratio, and enhanced fat accumulation. The epicardium of aged FMT recipients shows fat accumulation, accompanied by cardiomyocyte hypertrophy, cardiac fibrosis and increased cellular apoptosis. Mechanistically, aged FMT suppresses the PPARα/PGC1α signaling pathway in HF. Notably, activation of PPARα effectively rescues the metabolic changes and myocardial injury caused by aged FMT. In conclusion, our study emphasizes the role of the PPARα/PGC1α signaling pathway in aged FMT-mediated HF.

Understanding photochemical degradation mechanisms in photoactive layer materials for organic solar cells.

Over the past decades, the field of organic solar cells (OSCs) has witnessed a significant evolution in materials chemistry, which has resulted in a remarkable enhancement of device performance, achieving efficiencies of over 19%. The photoactive layer materials in OSCs play a crucial role in light absorption, charge generation, transport and stability. To facilitate the scale-up of OSCs, it is imperative to address the photostability of these electron acceptor and donor materials, as their photochemical degradation process remains a challenge during the photo-to-electric conversion. In this review, we present an overview of the development of electron acceptor and donor materials, emphasizing the crucial aspects of their chemical stability behavior that are linked to the photostability of OSCs. Throughout each section, we highlight the photochemical degradation pathways for electron acceptor and donor materials, and their link to device degradation. We also discuss the existing interdisciplinary challenges and obstacles that impede the development of photostable materials. Finally, we offer insights into strategies aimed at enhancing photochemical stability and discuss future directions for developing photostable photo-active layers, facilitating the commercialization of OSCs.

Efficacy and safety of electroacupuncture for insomnia: A systematic review and meta-analysis.

BACKGROUND: Electroacupuncture is often used to treat insomnia. OBJECTIVE: To evaluate the efficacy and safety of electroacupuncture for insomnia. SEARCH STRATEGY: Databases including PubMed, Cochrane Library, Embase, Web of Science, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang Data and VIP Full-text e-Journals Database were searched up to January 15, 2023. INCLUSION CRITERIA: Randomized clinical trials were included if they compared the clinical efficacy and safety of electroacupuncture with sham acupuncture, no treatment or usual care (UC) and general acupuncture. DATA EXTRACTION AND ANALYSIS: The full texts of the studies were reviewed to remove ineligible literature. The extracted data included authors, publication year, diagnostic criteria, sample size, population characteristics, interventions and outcomes. The above steps were performed independently by two reviewers and the data were cross-checked. Stata15.0 software was used to analyze the extracted outcome data. For continuous data (Pittsburgh Sleep Quality Index [PSQI] score and Insomnia Severity Index score), weighted mean difference (WMD) was calculated and 95% confidence interval (CI) was reported when the same scale was applied. For dichotomous variables (clinical response rate and adverse events), a meta-analysis was performed using risk ratio (RR) as the effect indicator. RESULTS: Thirty-one trials with 2226 subjects were included. The meta-analysis suggested that electroacupuncture was more effective in improving insomnia compared with the control group (sham acupuncture, no treatment, UC and general acupuncture) (RR = 1.21; 95% CI: [1.16, 1.27]), significantly reducing the PSQI score in insomnia patients after treatment and at follow-up (WMD = -3.23; 95% CI: [-4.29, -2.17]; P < 0.001). There was no significant difference in the incidence of adverse events between the EA and control groups (sham acupuncture and no treatment or UC. RR = 1.48; 95% CI: [0.91, 2.40]; P = 0.117). In addition, the regression results revealed that receiving electroacupuncture for seven to nine weeks provided the best efficacy (P < 0.05). CONCLUSION: Electroacupuncture can significantly promote better sleep quality in insomnia patients and is suitable for the treatment of various types of insomnia. However, the articles included were single-center trials with small sample sizes, and some articles were of poor quality. Therefore, further research is still needed to confirm these findings. Please cite this article as: Xu HY, Wu LN, Zhang Y, Ba T, Zhao XF. Efficacy and safety of electroacupuncture for insomnia: A systematic review and meta-analysis. J Integr Med. 2024; Epub ahead of print.

Combination of tumor antigen drainage and immune activation to promote a cancer-immunity cycle against glioblastoma.

While conventional cancer modalities, such as chemotherapy and radiotherapy, act through direct killing of tumor cells, cancer immunotherapy elicits potent anti-tumor immune responses thereby eliminating tumors. Nevertheless, promising outcomes have not been reported in patients with glioblastoma (GBM) likely due to the immune privileged status of the central nervous system and immunosuppressive micro-environment within GBM. In the past years, several exciting findings, such as the re-discovery of meningeal lymphatic vessels (MLVs), three-dimensional anatomical reconstruction of MLV networks, and the demonstration of the promotion of GBM immunosurveillance by lymphatic drainage enhancement, have revealed an intricate communication between the nervous and immune systems, and brought hope for the development of new GBM treatment. Based on conceptual framework of the updated cancer-immunity (CI) cycle, here we focus on GBM antigen drainage and immune activation, the early events in driving the CI cycle. We also discuss the implications of these findings for developing new therapeutic approaches in tackling fatal GBM in the future.

NOT gated T cells that selectively target EGFR and other widely expressed tumor antigens.

Here, we show that a NOT gated cell therapy (Tmod) can exploit antigens such as epidermal growth factor receptor (EGFR) and human leukocyte antigen-E (HLA-E) which are widely expressed on cancer cells. Noncancerous cells-despite high expression of these antigens-are protected from cytotoxicity by the action of an inhibitory receptor ("blocker") via a mechanism that involves blocker modulation of CAR surface expression. The blocker is triggered by the product of a polymorphic HLA allele (e.g., HLA-A∗02) deleted in a significant subset of solid tumors via loss of heterozygosity. Moreover, Tmod constructs that target mouse homologs of EGFR or HLA-E for activation, and a mouse-equivalent of HLA-A∗02 for inhibition, protect mice from toxicity caused by the CAR alone. The blocker also controls graft vs. host response in allogeneic T cells in vitro, consistent with the use of Tmod cells for off-the-shelf therapy without additional gene-editing.

Assessing the functional vulnerability of woody plant communities within a large scale tropical rainforest dynamics plot.

Introduction: Tropical forests are characterized by intricate mosaics of species-rich and structurally complex forest communities. Evaluating the functional vulnerability of distinct community patches is of significant importance in establishing conservation priorities within tropical forests. However, previous assessments of functional vulnerability in tropical forests have often focused solely on isolated factors or individual disturbance events, with limited consideration for a broad spectrum of disturbances and the responses of diverse species. Methods: We assessed the functional vulnerability of woody plant communities in a 60-ha dynamic plot within a tropical montane rainforest by conducting in silico simulations of a wide range disturbances. These simulations combined plant functional traits and community properties, including the distribution of functional redundancy across the entire trait space, the distribution of abundance across species, and the relationship between species trait distinctiveness and species abundance. We also investigated the spatial distribution patterns of functional vulnerability and their scale effects, and employed a spatial autoregressive model to examine the relationships between both biotic and abiotic factors and functional vulnerability at different scales. Results: The functional vulnerability of tropical montane rainforest woody plant communities was generally high (the functional vulnerability of observed communities was very close to that of the most vulnerable virtual community, with a value of 72.41% on average at the 20m×20m quadrat scale), and they exhibited significant spatial heterogeneity. Functional vulnerability decreased with increasing spatial scale and the influence of both biotic and abiotic factors on functional vulnerability was regulated by spatial scale, with soil properties playing a dominant role. Discussion: Our study provides new specific insights into the comprehensive assessment of functional vulnerability in the tropical rainforest. We highlighted that functional vulnerabilities of woody plant communities and their sensitivity to environmental factors varied significantly within and across spatial scales in the tropical rainforest landscape. Preserving and maintaining the functionality of tropical ecosystems should take into consideration the variations in functional vulnerability among different plant communities and their sensitivity to environmental factors.

Mechanisms of myeloid-derived suppressor cell-mediated immunosuppression in colorectal cancer and related therapies.

Severe immunosuppression is a hallmark of colorectal cancer (CRC). Myeloid-derived suppressor cells (MDSCs), one of the most abundant components of the tumor stroma, play an important role in the invasion, metastasis, and immune escape of CRC. MDSCs create an immunosuppressive microenvironment by inhibiting the proliferation and activation of immunoreactive cells, including T and natural killer cells, as well as by inducing the proliferation of immunosuppressive cells, such as regulatory T cells and tumor-associated macrophages, which, in turn, promote the growth of cancer cells. Thus, MDSCs are key contributors to the emergence of an immunosuppressive microenvironment in CRC and play an important role in the breakdown of antitumor immunity. In this narrative review, we explore the mechanisms through which MDSCs contribute to the immunosuppressive microenvironment, the current therapeutic approaches and technologies targeting MDSCs, and the therapeutic potential of modulating MDSCs in CRC treatment. This study provides ideas and methods to enhance survival rates in patients with CRC.

Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space.

Integrating multiple single-cell datasets is essential for the comprehensive understanding of cell heterogeneity. Batch effect is the undesired systematic variations among technologies or experimental laboratories that distort biological signals and hinder the integration of single-cell datasets. However, existing methods typically rely on a selected dataset as a reference, leading to inconsistent integration performance using different references, or embed cells into uninterpretable low-dimensional feature space. To overcome these limitations, a reference-free method, Beaconet, for integrating multiple single-cell transcriptomic datasets in original molecular space by aligning the global distribution of each batch using an adversarial correction network is presented. Through extensive comparisons with 13 state-of-the-art methods, it is demonstrated that Beaconet can effectively remove batch effect while preserving biological variations and is superior to existing unsupervised methods using all possible references in overall performance. Furthermore, Beaconet performs integration in the original molecular feature space, enabling the characterization of cell types and downstream differential expression analysis directly using integrated data with gene-expression features. Additionally, when applying to large-scale atlas data integration, Beaconet shows notable advantages in both time- and space-efficiencies. In summary, Beaconet serves as an effective and efficient batch effect removal tool that can facilitate the integration of single-cell datasets in a reference-free and molecular feature-preserved mode.

Pan-cancer identified ARPC1B as a promising target for tumor immunotherapy and prognostic biomarker, particularly in READ.

ARPC1B encodes the protein known as actin-related protein 2/3 complex subunit 1 B (ARPC1B), which controls actin polymerization in the human body. Although ARPC1B has been linked to several human malignancies, its function in these cancers remains unclear. TCGA, GTEx, CCLE, Xena, CellMiner, TISIDB, and molecular signature databases were used to analyze ARPC1B expression in cancers. Visualization of data was primarily achieved using R language, version 4.0. Nineteen tumors exhibited high levels of ARPC1B expression, which were associated with different tumor stages and significantly affected the prognosis of various cancers. The level of ARPC1B expression substantially connected the narrative of ARPC1B expression with several TMB cancers and showed significant changes in MSI. Additionally, tolerance to numerous anticancer medications has been linked to high ARPC1B gene expression. Using Gene Set Variation Analysis/Gene Set Enrichment Analysisanalysis and concentrating on Rectum adenocarcinoma (READ), we thoroughly examined the molecular processes of the ARPC1B gene in pan-cancer. Using WGCNA, we examined the co-expression network of READ and ARPC1B. Meanwhile, ten specimens were selected for immunohistochemical examination, which showed high expression of ARPC1B in READ. Human pan-cancer samples show higher ARPC1B expression than healthy tissues. In many malignancies, particularly READ, ARPC1B overexpression is associated with immune cell infiltration and a poor prognosis. These results imply that the molecular biomarker ARPC1B may be used to assess the prognosis and immune infiltration of patients with READ.

Anlotinib induces neuronal-like differentiation of neuroblastoma by downregulating CRMP5.

The therapeutic effect of anlotinib on neuroblastoma is still not fully understood. This study aims to explore the differentiation therapeutic effects of anlotinib on neuroblastoma and its potential association with the neural development regulatory protein collapsin response mediator protein 5 (CRMP5), both in vivo and in vitro. A patient-derived xenograft (PDX) model was established to observe the therapeutic effect of anlotinib. Neuroblastoma cell lines SK-N-SH and SK-N-AS were cultured to observe the morphological impact of anlotinib. Transwell assay was used to evaluate the cell invasion, and Western blot analysis and immunohistochemistry were employed to detect the expressions of neuronal differentiation-related proteins. Results indicate that anlotinib effectively inhibited tumor growth in the PDX model, modulated the expressions of neuronal differentiation markers. In vitro, anlotinib treatment induced neurite outgrowth in neuroblastoma cells and inhibited their invasive ability, reflecting a change in neuronal marker expression patterns consistent with the PDX model. Similarly, in the SK-N-AS mouse xenograft model, anlotinib demonstrated comparable tumor-suppressing effects and promoted neuronal-like differentiation. Additionally, anlotinib significantly downregulated CRMP5 expression in neuroblastoma both in vivo and in vitro. Overexpression of CRMP5 significantly reversed the differentiation therapy effect of anlotinib, exacerbating the aggressiveness and reducing the differentiation level of neuroblastoma. These findings highlight the potential of anlotinib as an anti-neuroblastoma agent. It may suppress tumor proliferation and invasion by promoting the differentiation of tumor cells towards a neuronal-like state, and this differentiation therapy effect involves the inhibition of CRMP5 signaling.

The basal forebrain to lateral habenula circuitry mediates social behavioral maladaptation.

Elucidating the neural basis of fear allows for more effective treatments for maladaptive fear often observed in psychiatric disorders. Although the basal forebrain (BF) has an essential role in fear learning, its function in fear expression and the underlying neuronal and circuit substrates are much less understood. Here we report that BF glutamatergic neurons are robustly activated by social stimulus following social fear conditioning in male mice. And cell-type-specific inhibition of those excitatory neurons largely reduces social fear expression. At the circuit level, BF glutamatergic neurons make functional contacts with the lateral habenula (LHb) neurons and these connections are potentiated in conditioned mice. Moreover, optogenetic inhibition of BF-LHb glutamatergic pathway significantly reduces social fear responses. These data unravel an important function of the BF in fear expression via its glutamatergic projection onto the LHb, and suggest that selective targeting BF-LHb excitatory circuitry could alleviate maladaptive fear in relevant disorders.

Hydrogen peroxide serves as pivotal fountainhead for aerosol aqueous sulfate formation from a global perspective.

Traditional atmospheric chemistry posits that sulfur dioxide (SO2) can be oxidized to sulfate (SO42-) through aqueous-phase reactions in clouds and gas-phase oxidation. Despite adequate knowledge of traditional mechanisms, several studies have highlighted the potential for SO2 oxidation within aerosol water. Given the widespread presence of tropospheric aerosols, SO42- production through aqueous-phase oxidation in aerosol water could have a pervasive global impact. Here, we quantify the potential contributions of aerosol aqueous pathways to global sulfate formation based on the GEOS-Chem simulations and subsequent theoretical calculations. Hydrogen peroxide (H2O2) oxidation significantly influences continental regions both horizontally and vertically. Over the past two decades, shifts in the formation pathways within typical cities reveal an intriguing trend: despite reductions in SO2 emissions, the increased atmospheric oxidation capacities, like rising H2O2 levels, prevent a steady decline in SO42- concentrations. Abating oxidants would facilitate the benefit of SO2 reduction and the positive feedback in sulfate mitigation.

Distinct patterns of monocular advantage for facial emotions in social anxiety.

Individuals with social anxiety often exhibit atypical processing of facial expressions. Previous research in social anxiety has primarily emphasized cognitive bias associated with face processing and the corresponding abnormalities in cortico-limbic circuitry, yet whether social anxiety influences early perceptual processing of emotional faces remains largely unknown. We used a psychophysical method to investigate the monocular advantage for face perception (i.e., face stimuli are better recognized when presented to the same eye compared to different eyes), an effect that is indicative of early, subcortical processing of face stimuli. We compared the monocular advantage for different emotional expressions (neutral, angry and sad) in three groups (N = 24 per group): individuals clinically diagnosed with social anxiety disorder (SAD), individuals with high social anxiety in subclinical populations (SSA), and a healthy control (HC) group of individuals matched for age and gender. Compared to SSA and HC groups, we found that individuals with SAD exhibited a greater monocular advantage when processing neutral and sad faces. While the magnitudes of monocular advantages were similar across three groups when processing angry faces, individuals with SAD performed better in this condition when the faces were presented to different eye. The former findings suggest that social anxiety leads to an enhanced role of subcortical structures in processing nonthreatening expressions. The latter findings, on the other hand, likely reflect an enhanced cortical processing of threatening expressions in SAD group. These distinct patterns of monocular advantage indicate that social anxiety altered representation of emotional faces at various stages of information processing, starting at an early stage of the visual system.

[A multicenter study of neonatal stroke in Shenzhen, China]. / 深圳市新生儿脑卒中多中心现况调查.

OBJECTIVES: To investigate the incidence rate, clinical characteristics, and prognosis of neonatal stroke in Shenzhen, China. METHODS: Led by Shenzhen Children's Hospital, the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022. The incidence, clinical characteristics, treatment, and prognosis of neonatal stroke in Shenzhen were analyzed. RESULTS: The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137, 1/6 060, and 1/7 704, respectively. Ischemic stroke accounted for 75% (27/36); boys accounted for 64% (23/36). Among the 36 neonates, 31 (86%) had disease onset within 3 days after birth, and 19 (53%) had convulsion as the initial presentation. Cerebral MRI showed that 22 neonates (61%) had left cerebral infarction and 13 (36%) had basal ganglia infarction. Magnetic resonance angiography was performed for 12 neonates, among whom 9 (75%) had involvement of the middle cerebral artery. Electroencephalography was performed for 29 neonates, with sharp waves in 21 neonates (72%) and seizures in 10 neonates (34%). Symptomatic/supportive treatment varied across different hospitals. Neonatal Behavioral Neurological Assessment was performed for 12 neonates (33%, 12/36), with a mean score of (32±4) points. The prognosis of 27 neonates was followed up to around 12 months of age, with 44% (12/27) of the neonates having a good prognosis. CONCLUSIONS: Ischemic stroke is the main type of neonatal stroke, often with convulsions as the initial presentation, involvement of the middle cerebral artery, sharp waves on electroencephalography, and a relatively low neurodevelopment score. Symptomatic/supportive treatment is the main treatment method, and some neonates tend to have a poor prognosis.

Advances in the study of tertiary lymphoid structures in the immunotherapy of breast cancer.

Breast cancer, as one of the most common malignancies in women, exhibits complex and heterogeneous pathological characteristics across different subtypes. Triple-negative breast cancer (TNBC) and HER2-positive breast cancer are two common and highly invasive subtypes within breast cancer. The stability of the breast microbiota is closely intertwined with the immune environment, and immunotherapy is a common approach for treating breast cancer.Tertiary lymphoid structures (TLSs), recently discovered immune cell aggregates surrounding breast cancer, resemble secondary lymphoid organs (SLOs) and are associated with the prognosis and survival of some breast cancer patients, offering new avenues for immunotherapy. Machine learning, as a form of artificial intelligence, has increasingly been used for detecting biomarkers and constructing tumor prognosis models. This article systematically reviews the latest research progress on TLSs in breast cancer and the application of machine learning in the detection of TLSs and the study of breast cancer prognosis. The insights provided contribute valuable perspectives for further exploring the biological differences among different subtypes of breast cancer and formulating personalized treatment strategies.