Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

ObjectiveIn nature, objects cast shadows due to illumination, forming the basis for stereoscopic perception. Birds need to adapt to changes in lighting (meaning they can recognize stereoscopic shapes even when shadows look different) to accurately perceive different three-dimensional forms. However, how neurons in the key visual brain area in birds handle these lighting changes remains largely unreported. In this study, pigeons (Columba livia) were used as subjects to investigate how neurons in pigeon’s ventrolateral mesopallium (MVL) represent stereoscopic shapes consistently, regardless of changes in lighting. MethodsVisual cognitive training combined with neuronal recording was employed. Pigeons were first trained to discriminate different stereoscopic shapes (concave/convex). We then tested whether and how light luminance angle and surface appearance of the stereoscopic shapes affect their recognition accuracy, and further verify whether the results rely on specify luminance color. Simultaneously, neuronal firing activity of neurons was recorded with multiple electrode array implanted from the MVL during the presentation of difference shapes. The response was finally analyzed how selectively they responded to different stereoscopic shapes and whether their selectivity was affected by the changes of luminance condition (like lighting angle) or surface look. Support vector machine (SVM) models were trained on neuronal population responses recorded under one condition (light luminance angle of 45°) and used to decode responses under other conditions (light luminance angle of 135°, 225°, 315°) to verify the invariance of responses to different luminance conditions. ResultsBehavioral results from 6 pigeons consistently showed that the pigeons could reliably identify the core 3D shape (over 80% accuracy), and this ability wasn’t affected by changes in light angle or surface appearance. Statistical analysis of 88 recorded neurons from 6 pigeons revealed that 83% (73/88) showed strong selectivity for specific 3D shapes (selectivity index>0.3), and responses to convex shapes were consistently stronger than to concave shapes. These shape-selective responses remained stable across changes in light angle and surface appearance. Neural patterns were consistent under both blue and orange lighting. The decoding accuracy achieves above 70%, suggesting stable responses under different conditions (e.g., different lighting angles or surface appearance). ConclusionNeurons in the pigeon MVL maintain a consistent neural encoding pattern for different stereoscopic shapes, unaffected by illumination or surface appearance. This ensures stable object recognition by pigeons in changing visual environments. Our findings provide new physiological evidence for understanding how birds achieve stable perception (“invariant neural representations”) while coping with variations in the visual field.

BACKGROUND: Telesurgery has the potential to overcome spatial limitations for surgeons, which depends on surgical robot and the quality of network communication. However, the influence of network latency and bandwidth on telesurgery is not well understood. METHODS: A telesurgery system capable of dynamically adjusting image compression ratios in response to bandwidth changes was established between Beijing and Sanya (Hainan province), covering a distance of 3000 km. In total, 108 animal operations, including 12 surgical procedures, were performed. Total latency ranging from 170 ms to 320 ms and bandwidth from 15-20 Mbps to less than 1 Mbps were explored using designed surgical tasks and hemostasis models for renal vein and internal iliac artery rupture bleeding. Network latency, jitter, frame loss, and bit rate code were systemically measured during these operations. National Aeronautics and Space Administration Task Load Index (NASA-TLX) and a self-designed scale measured the workload and subjective perception of surgeons. RESULTS: All 108 animal telesurgeries, conducted from January 2023 to June 2023, were performed effectively over a total duration of 3866 min. The operations were completed with latency up to 320 ms and bandwidths as low as 1-5 Mbps. Hemostasis for vein and artery rupture bleeding models was effectively achieved under these low bandwidth conditions. The NASA-TLX results indicated that latency significantly impacted surgical performance more than bandwidth and image clarity reductions. CONCLUSIONS This telesurgery system demonstrated safety and reliability. A total of 320 ms latency is acceptable for telesurgery operations. Reducing image clarity can effectively mitigate the potential latency increase caused by decreased bandwidth, offering a new method to reduce the impact of latency on telesurgery.
Animals ; Robotic Surgical Procedures/methods* ; Laparoscopy/methods*