Natural killer (NK) cells are promising platforms for off-the-shelf immunotherapy, yet nonviral precision engineering remains limited by poor HDR efficiency, DNA toxicity, and manufacturing challenges. The aim of this study was to establish a high-yield, nonviral knock-in platform. Through extensive in-depth rational screens, we achieved ∼90% HDR insertion of therapeutic payloads while maintaining 100% postediting recovery. By hijacking endogenous transcriptional programs, we installed genetic circuits into defined genomic loci to tune transgene expression. To enable context-dependent therapeutic responses, we integrated a synthetic positive feedback circuit at the CISH locus, which enhanced NK cell persistence and drove strong expression of anti-CD22/19 dual CAR. A hypoxia-responsive IL-12 circuit gated by the PFKFB4 promoter restored cytotoxicity under environmental stress. Finally, we showed this platform is compatible with GMP manufacturing and supports clinical-scale expansion. These findings provide a scalable framework for programmable, nonviral editing of NK cell effector functions for therapeutic and research applications.
To develop and validate machine learning (ML) models for predicting early postoperative corneal edema (CE) after phacoemulsification in patients with normal preoperative corneal endothelium. A retrospective cohort study analyzed data from 1128 eyes undergoing uncomplicated phacoemulsification at Tianjin Medical University Eye Hospital (May 2024-May 2025). CE was diagnosed on postoperative day 1 based on central corneal thickness increase > 50 μm, central stromal opacification, and blurred iris texture. Lasso regression preliminarily screened 26 clinical features to 9 key variables. Eleven ML models and a logistic regression model were developed. A hybrid Recursive Feature Elimination and Exhaustive Search strategy identified optimal feature subsets. Model performance is evaluated using metrics such as Area Under the Curve (AUC), accuracy, sensitivity, specificity, and Brier Score. Key predictors consistently identified included cumulative dissipated energy (CDE), age, and lens nucleus hardness. The optimized Support Vector Machine (SVM) model demonstrated superior performance during internal validation (AUC = 0.92, accuracy = 91.56%) and maintained strong generalizability on the independent test set (AUC = 0.89, accuracy = 84.50%). Other models like GradientBoost and PLS-DA also showed good performance post-optimization. The traditional LR model underperformed (optimized AUC = 0.81). ML models, particularly SVM, effectively predict postoperative CE risk in cataract patients with normal corneal endothelium. CDE, age, and nucleus hardness are critical predictors. The SVM model provides a robust, preoperative tool for predicting individual risk of postoperative CE. By identifying high-risk patients, it has the potential to guide surgical technique selection, optimize patient counseling, and streamline postoperative care pathways, thereby enhancing overall surgical quality and patient satisfaction.
Prolyl hydroxylase domain enzyme 1 (PHD1) is a key regulator of hypoxic adaptation and metabolic homeostasis, playing an important role in tissue damage and repair. To enable precise pharmacological interrogation of PHD1 function, we developed the first PHD1 degrader using proteolysis-targeting chimera (PROTAC) technology. Our lead compound, SH-26, a cereblon (CRBN)-recruiting PROTAC, induced PHD1 degradation in a concentration-, time-, and ubiquitin-proteasome system (UPS)-dependent manner across multiple cell lines. In an acetaminophen (APAP)-induced acute liver injury (ALI) model, SH-26 demonstrated protective effects, attenuating hepatic inflammation and necrosis without detectable cytotoxicity. Mechanistically, SH-26-mediated PHD1 degradation attenuated APAP-triggered reactive oxygen species (ROS) accumulation, mitochondrial dysfunction, and NLRP3 inflammasome activation, leading to robust in vivo protection against ALI. Collectively, our work identifies SH-26 as the first effective PHD1 degrader and demonstrates its utility as a chemical tool to dissect the pathological role of PHD1 in ALI.
Nurses are the backbone of the health care service team, and having a stable team of nurses is critical to effective team operations. Organizational commitment helps nurses remain in their current organization and facilitates the attainment of organizational goals. Understanding the organizational commitment of nurses and its influencing factors is necessary. This study was conducted to identify the latent characteristics affecting the level of organizational commitment in nurses and explore their influencing factors to provide feasible recommendations for improving hospital nursing management measures. From November 2023 to February 2024, 1,037 nurses from hospitals in Beijing, Changsha (Hunan Province), and Jinhua (Zhejiang Province) participated in this study. The data were collected using a socio-demographic information questionnaire, Organizational Commitment Scale, Global Job Embeddedness Items, and Caring Assessment Tool-administration. Data analysis included latent profile analysis, χ2 test, analysis of variance, and multifactorial logistic regression. The level of organizational commitment may be classified into four distinct profiles, namely Observers (n=95, 9.16%), Stabilizers (n=319, 30.76%), Aspirants (n=369, 35.58%), and Stalwarts (n=254, 24.49%). The results of this study showed that higher levels of perceived management care, job embeddedness, and salary satisfaction, earning a lower monthly income, longer years of service, having children, and being employed in a permanent position were positively associated with higher organizational commitment. The findings indicate that organizational commitment in nurses is affected by factors including self-perceived management care, job embeddedness, salary satisfaction, employment form, whether they have children, monthly income, and years of service. The results of this study provide evidence that hospital nursing managers may reference in enhancing measures to strengthen the organizational commitment of nurses, which may include improving humane management practices and the work environment as well as rationalizing income distribution and human resources allocation, thereby promoting nurses' identification with organizational goals, increasing retention, and enhancing the quality of nursing services and patient satisfaction.
Human anatomy is the cornerstone of medicine. Currently, there is a lack of effective learning tools that can establish a correlation between 2D sectional anatomy and 3D stereoscopic anatomy and facilitate the conversion between the two. This study aimed to evaluate the efficacy of the Imaging Anatomy Virtual Simulation Experiment (IAVSE) course in undergraduate education. This nonrandomized controlled trial was conducted with 102 third-year medical students from the 2017 and 2018 cohorts: 50 medical students who elected to take the IAVSE course were assigned to the experimental group, and 52 students who took the traditional laboratory course served as the control group. Primary outcomes assessed by teaching evaluation included the third-year human anatomy theory scores and fourth-year medical imaging theory, practical test, and total scores. The secondary outcome was a 7-item Likert scale questionnaire based on Bloom's Taxonomy of Educational Objectives. Statistical analyses were performed using SPSS (IBM Corp), with the independent samples t test applied for normally distributed continuous data and the Mann-Whitney U test for nonnormally distributed data. A two-tailed P<.05 was considered statistically significant for all tests. The results of the teaching evaluation indicated a statistically significant difference between the experimental group and the control group. The experimental group achieved higher scores in human anatomy theory (experimental group: median 85, IQR 84.25-85.50, control group: median 81.75, IQR 78.13-83.00; P<.001), medical imaging theory (experimental group: median 61.03, IQR 60.41-61.53, control group: median 59.03, IQR 55.66-59.53; P<.001), practical testing (experimental group: median 22.50, IQR 21.50-23.00, control group: median 20.50, IQR 19.00-22.00; P<.001), and total scores (experimental group: mean 83.26, SD 2.58; control group: mean 78.46, SD 3.76; P<.001). Student feedback collected via a Likert questionnaire also revealed significantly higher ratings in the experimental group across multiple domains, including enjoyment, interactivity, participation, satisfaction, learning efficiency, usability, and acceptance (all P values <.001, except for serviceability, P=.02). Furthermore, the experimental group demonstrated a higher level of acceptance toward the virtual simulation course. The IAVSE course effectively bridges the gap between human anatomy and medical imaging. It enhances students' spatial understanding and academic performance and stimulates their learning interest. It thus holds significant potential for broader application in undergraduate medical education.
Owing to their high surface areas and structural tunability, metal-organic frameworks (MOFs) offer an ideal platform for stabilizing nanocatalysts within their well-defined pores. In this work, we report the synthesis of a zinc-based MOF, FICN-13, with a tris(pyrazolate) ligand tris[4-(1H-pyrazol-4-yl)phenyl]amine (H3TPPA). With a dual-solvent approach, copper oxide nanoparticles were deposited within the one-dimensional channels and on the external surface of FICN-13, forming an integrated MOF-CuOx heterojunction. Incorporation of CuOx nanoparticles led to a product selectivity shift from CO to CH4 in photocatalytic CO2 reduction, achieving a methane production of 56.12 μmol·g-1 and a selectivity of 62% and representing a 195% enhancement over pristine FICN-13. In situ infrared spectroscopy further revealed a stepwise hydrogenation pathway via *CO2 → *CO → *CHO → *CH3O → CH4.
High-yielding dairy cows often experience metabolic stress during early lactation, leading to subclinical ketosis (SCK) and reproductive impairment. This study investigates how SCK-associated conditions (hypoglycemia and elevated nonesterified fatty acids, NEFA) affect bovine granulosa cell (GC) function via the PI3K/AKT pathway. Primary GCs were cultured under four metabolic conditions for 24 h: normal glucose (NG), low glucose (LG), NG + high NEFA, and LG + high NEFA. Additional groups treated with the PI3K/AKT activator SC79 or inhibitor LY294002 under LG + NEFA stress were included. Combined LG + NEFA stress reduced cell viability, increased apoptosis, impaired steroidogenesis, and disrupted mitochondrial function. While LG alone increased p-AKT, NEFA alone suppressed this. SC79 rescued these effects, whereas LY294002 exacerbated them. These findings demonstrate that metabolic stressors disrupt GC proliferation, steroidogenesis, and mitochondrial homeostasis through PI3K/AKT pathway dysregulation, offering insights into the SCK-associated reproductive dysfunction.
The simultaneous and deep sequestration of multivalent antimony (Sb(III) and Sb(V)) from aquatic environments is strictly hindered by the "site-shielding effect", where the random agglomeration of functional groups limits active site accessibility. To address this, a novel supramolecular microcrystal-functionalized biochar (CPPB) was engineered by anchoring L-cysteine and polyethyleneimine onto a lignin-derived biochar matrix. Structural analysis confirmed the in-situ growth of well-ordered hexagonal L-cystine microcrystals within the hierarchical pores. CPPB exhibited exceptional maximum adsorption capacities of 513.5 mg/g for Sb(III) and 500.9 mg/g for Sb(V), with > 90% of the total capacity achieved within 10 min. The material maintained robust performance across a pH range of 3.0-8.0 and demonstrated high selectivity in complex wastewater matrices. Mechanistic investigations, integrating density functional theory calculations and multiscale spectroscopic analyses, unveiled a unique adsorption-induced topological transformation. Specifically, the intense coordination affinity between Sb species and active sites overcomes the lattice energy, triggering a transition of L-cystine from long-range ordered crystalline domains to short-range disordered open networks. This dynamic reconstruction effectively exposes previously shielded high-density sites (-SH, -NH, and -COO⁻) for multidentate coordination. Furthermore, the Sb-saturated CPPB was successfully upcycled into an SbPO4/C composite via in-situ carbonization; as a sodium-ion battery anode, this recovered material delivered a stable capacity of 261.0 mA h/g after 60 cycles. This work provides a transformative strategy to unlock the latent thermodynamic potential of biochar-based materials and establishes a sustainable "waste-to-resource" closed-loop for heavy metal remediation.
Artificial intelligence (AI) is increasingly used in healthcare but often lacks clinician and patient trust. Explainable AI (XAI) aims to clarify predictions and to make AI decisions more transparent, interpretable, and clinically actionable. Yet, current methods fall short. In this Perspective, we argue that, for XAI to be clinically useful in medical imaging and to build trust with clinicians, it must satisfy three guiding principles: technical robustness, adaptation to end users, and alignment of explanations with the specific clinical task. We introduce a conceptual framework, incorporating these principles, to guide future XAI design and deployment based on expectations and shared responsibilities for developers, vendors, and healthcare institutions. By ensuring robustness, personalizing outputs, and aligning explanations with use cases, XAI can move beyond one-size-fits-all approaches to task- and user-centered design, to support effective and trustworthy AI adoption in healthcare.
Nanoscale lasers with low thresholds and on-demand structured light output are essential for compact integrated photonic technology. Introducing engineered disorder into high quality-factor (Q) resonant cavities emerges as a promising route, yet the inaccurate disorder-to-phase correspondence and the limited symmetry breaking mechanisms restrict the achievable optical structures in output lasers. Here, by revealing translational disorder and rotational disorder as two decoupled symmetry-breaking mechanisms, we propose disorder-on-disorder (DoD) meta-cavities that allow for customizing eigenmodes for multichannel lasing emission control while preserving high-Q resonances. In the experiment, we structure perovskite into fully monolithic DoD meta-cavities to maximize mode-gain overlap and demonstrate structured lasing with low threshold (~7 microjoules per square centimeter), high Q (~103), and diverse structured laser arrays including phase/polarization vortices, one-dimensional and two-dimensional Airy beams, and Hermite- and Laguerre-Gaussian beams. Our findings highlight DoD meta-cavity as a distinct and generalized route to compact monolithic high-Q photonic devices, opening opportunities in structured lasers, nonlinear optics, and integrated quantum photonics.
Post-transplant relapse remains a major clinical challenge in Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph + ALL). Real-time quantitative PCR (RQ-PCR) for BCR::ABL1 is the current standard for measurable residual disease (MRD) monitoring, whereas digital PCR (dPCR) offers substantially higher analytical sensitivity. Whether this increased sensitivity translates into additional prognostic value after allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains unclear. In this prospective study (NCT06211166), 270 patients with Ph + ALL were longitudinally monitored after allo-HSCT. MRD was assessed in parallel using dPCR, RQ-PCR, and MFC. Based on the first post-transplant MRD detection pattern, patients were categorized into four groups: double-negative (n = 80), dPCR-single-positive (n = 158), RQ-PCR-single-positive (n = 3), and double-positive (n = 29). The dPCR-single-positive pattern was the most prevalent MRD status, accounting for 58.5% of patients. dPCR positivity independently predicted subsequent MFC-MRD conversion (HR 9.56, P = 0.029), with a median lead time of 77 days. In addition, dPCR detected BCR::ABL1 positivity earlier than RQ-PCR, preceding subsequent hematologic relapse by a median of 64.5 and 91.5 days, respectively. However, the cumulative incidence of hematologic relapse (CIR), the primary endpoint of this study, did not differ significantly among the four MRD-defined groups (P = 0.60). Consistently, isolated dPCR positivity was not associated with inferior 2-year leukemia-free survival (LFS; P = 0.30) or overall survival (OS; P = 0.60). Although dPCR detects molecular disease earlier and anticipates MFC-MRD by 2 months after allo-HSCT in Ph + ALL, isolated ultra-low-level BCR::ABL1 positivity does not impact relapse risk, LFS, or OS. Routine MRD monitoring with RQ-PCR plus MFC remains sufficient for prognostic stratification, while dPCR primarily provides an ultra-early signal to guide timely intervention rather than improving survival prediction.
Over 90% of nurse practitioners (NPs) are employed in hospitals in Taiwan. The influence of different practice environments and manager leadership styles on NP interprofessional collaboration and quality of care in acute care hospitals has been inadequately studied. This study was designed to investigate the influence of practice environment and leadership style on NP interprofessional collaboration and the quality of care they provide in acute care settings. A cross-sectional design and a national online survey were employed to collect data from 1,198 NPs who are members of the Taiwan Association of Nurse Practitioners (TANP). The measures utilized in this study include the Nurse Practitioner Acute Care Organizational Climate Questionnaire, the Multifactor Leadership Questionnaire-Form 6S, and the Provider-Perceptions of Team Effectiveness Questionnaire (Provider-PTE). A multiple regression model was applied to identify the factors potentially associated with interprofessional collaboration and quality of care. Physician relations and professional visibility were identified as the two most critical factors within the practice environment, enhancing interprofessional collaboration and quality of care, and "management with expectation" was identified as a key leadership strategy for improving both outcomes. These three factors accounted for 44.8% and 30.6% of the respective variances in NP interprofessional collaboration and quality of care. Improving practice-environment factors such as relationship with physicians and professional visibility, as well as managing NPs using an expectations-based leadership style, offer the potential to significantly enhance NP interprofessional collaboration and the quality of care they provide. Health care organizations may consider developing policies that focus on improving the practice environment as well as implementing transactional leadership styles to promote NP interprofessional collaboration and the quality of care they provide.
The provisioning of royal jelly for developing larvae by nurse bees is fundamental to social interaction in honey bee colonies. While royal jelly production is regulated by collective larval demand, it remains unclear how colony-level needs are translated into individual worker behavior. Here, we show that the larval pheromone E-β-ocimene (EBO), a volatile compound also used by pollinators as a floral food cue, elicits an intrinsic craving for protein in nurse bees that drives increased pollen consumption. Through in vitro and in vivo experiments, we demonstrate that this response is mediated by the leucokinin (Lk) and leucokinin receptor (Lkr) system, acting through the PKA-CREB-IRS signaling pathway to modulate the expression of the insulin receptor substrate gene (Irs). Elevated pollen intake then promotes the enlargement of the hypopharyngeal glands and enhanced production of major royal jelly proteins. Our findings uncover a molecular mechanism linking larval signaling to worker nutrition, highlighting how social bonds between honey bee larvae and nurses are rooted in ancestral pathways of protein hunger that predate eusociality.
To investigate the physiological status of Yangtze finless porpoises (YFPs) in Poyang Lake and assess health conditions across different habitats at a mesoscale geographical level, physical examination data from 25 individuals were collected from two habitats: Piaotou (PT, 19 individuals), Jinxi Lake (JX, 6 individuals). Independent samples t-test and Mann-Whitney U test were used to compare blood parameters between PT and JX population. Robust M-estimation was applied to conduct stratified tests on the independent effects of factors. Robust PCA was used to characterize the overall physiological differences between the two habitats. Using the ranges of healthy YFPs blood parameters as the reference group, Games-Howell test was used for multiple group comparisons. Results revealed significant differences in physiological status between YFPs inhabiting Piaotou and Jinxi Lake. Piaotou population exhibit better physiological status, characterized by higher oxygen-carrying capacity, nutritional status, and metabolic activity levels, while those in Jinxi Lake showed enhanced coagulation function or inflammatory responses. In hematological parameters, the PT population showed significantly higher red blood cell-related indices than the JX's. The JX population exhibited higher platelet-related parameters and extremely low Eosinophil counts and percentages. More parameters in the JX population differed significantly from the range of healthy physiological indicators, with Monocyte count and percentage, and Plateletcrit exceeding normal physiological ranges. For blood biochemical parameters, Aspartate amino Transferase and Triglyceride in the PT population, and Alkaline Phosphatase and Triglyceride in the JX population exceeded reference ranges. This study revealed significant physiological differences among YFPs inhabiting different habitats within the same lake system, indicating that the Piaotou population can serve as high-quality germplasm resources, while the Jinxi Lake population shows certain health risks in their physiological status.
The presence of upper limb dysfunction is a common complication following surgical interventions for breast cancer patients. This study aims to investigate the impact of digital rehabilitation therapy on the recovery of upper limb function in breast cancer patients after surgery. This research enrolled 52 breast cancer patients who underwent modified radical mastectomy at the Affiliated Xinhua Hospital of Shanghai Jiao Tong University School of Medicine between September 2022 and October 2023. A comparative analysis was conducted between the control group and the experimental group regarding their upper limb movements (flexion, extension, abduction, adduction), as well as their quality of life indicators. Following rehabilitation training, the extent of improvement in flexion, extension, abduction, and adduction of the affected upper limbs in the experimental group was significantly higher than that observed in the control group (p < 0.05). Notably, after the same 6-week period, the range of motion in flexion and abduction of the affected limbs in the experimental group did not significantly differ from that of their contralateral limbs (p > 0.05). According to scores on the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30, the experimental group also showed significant improvements in role functioning, emotional functioning, and social functioning compared to the control group (p < 0.05). The application of digital rehabilitation therapy in the recovery process of upper limb function among breast cancer patients post-surgery has proven efficacious in enhancing objective recovery of shoulder range of motion and improving several domains of quality of life, although no significant between-group differences were observed in patient-reported functional outcomes. Chinese Clinical Trial Registry (ChiCTR), ChiCTR2500107529, registered on August 13, 2025.
Myocardial ischemia-reperfusion (MI/R) injury significantly limits the clinical benefits of coronary reperfusion therapy. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has been implicated in myocardial ischemia-reperfusion (I/R) injury. Liproxstatin-1 (Lip-1) is a potent ferroptosis inhibitor, but its dynamic, dose-dependent effects on key molecular pathways and pathological hallmarks in the heart remain incompletely characterized. To systematically investigate the dose- and time-dependent cardioprotective effects of Lip-1 against myocardial I/R injury, with a focus on the NRF2/GPX4 pathway, iron deposition, and lysosomal integrity. Ninety Wistar rats were randomly allocated to 15 experimental groups (n = 6 per group): Normal (no surgery), Sham (thoracotomy without ischemia), I/R model, and I/R + Lip-1 treatment groups. Lip-1 was administered intravenously at doses of 1, 3, or 5 mg/kg at 0, 24, 48, and 72 h post-reperfusion initiation, with myocardial tissue and blood samples harvested 6 h after each injection. Cardiac function was assessed by echocardiography. Myocardial infarct size was determined by Evans Blue/TTC double staining. Serum levels of CK-MB and LDH were measured as markers of myocardial injury. Analyses included Western blot for NRF2 and GPX4 expression, Prussian blue staining for iron deposition quantification, and immunofluorescence for LAMP1 localization and intensity. Statistical analysis was performed using two-way ANOVA with Tukey's post hoc test for Lip-1 treatment groups, and t-tests or one-way ANOVA for model validation comparisons. Compared to Sham, I/R injury significantly decreased LVEF, increased infarct size, and elevated CK-MB and LDH levels (all P < 0.0001), confirming successful model establishment. It also downregulated GPX4 expression, induced severe iron deposition, and reduced LAMP1 levels, while triggering an adaptive upregulation of NRF2. Lip-1 treatment produced dose- and time-dependent protection across all measured endpoints. It improved cardiac function, reduced infarct size, and attenuated CK-MB and LDH release, with significant dose×time interactions for infarct size (F(6,60) = 8.338, P < 0.0001), CK-MB (F(6,60) = 6.467, P < 0.0001), and LDH (F(6,60) = 9.021, P < 0.0001). It dynamically modulated the NRF2/GPX4 axis, with peak GPX4 expression observed following the 48-hour administration (sampled at 54 h post-reperfusion). Lip-1 progressively reduced iron deposition, with maximal effect observed after the 72-hour administration (sampled at 78 h post-reperfusion), and rescued LAMP1 downregulation in later sampling points. Statistical analysis revealed significant dose×time interactions for NRF2 (F(6,60) = 200.8, p < 0.0001), GPX4 (F(6,60) = 34.84, p < 0.0001), and iron deposition. High-dose Lip-1 (5 mg/kg) demonstrated superior and sustained efficacy across all parameters. Lip-1 confers multi-faceted cardioprotection against I/R injury through sequential mechanisms involving early potentiation of the NRF2/GPX4 antioxidant defense, progressive attenuation of pathological iron accumulation, and restoration of lysosomal membrane integrity. The strict dose and temporal dependency of these effects provide critical insights for optimizing ferroptosis-targeted therapeutic strategies in ischemic heart disease.
Allostery plays a critical role in protein dynamics and is essential for many biological functions. Over the past decade, various computational approaches have been proposed for predicting allosteric sites. However, the strengths and weaknesses of each method are not well understood. In this study, we created two independent datasets that had not been used in selected computational protocols: a CAPASP-General subset comprising holo state allosteric proteins and a CAPASP-Unbound subset comprising apo state allosteric proteins. We then systematically evaluated the accuracy of five allosteric site prediction tools across five dimensions: sensitivity, specificity, F1-score, MCC value and ranking capability. The results indicated that the machine learning models PASSer and APOP, which are based on protein physicochemical properties, not only achieved the highest success rate in sensitivity prediction but also lead in average F1-score and MCC value. However, these models performed better with the CAPASP-General subset than with the CAPASP-Unbound subset, suggesting that the prediction models require further improvement. These findings could facilitate the selection of appropriate prediction models for different allosteric proteins and enhance our understanding of protein function and regulatory mechanisms.
Advances in biofabrication, stem cell biology, and biomaterials engineering have enabled the generation of multicellular tissue constructs capable of recapitulating key aspects of biological function. Despite these advances, the transition from millimeter-scale engineered tissues to centimeter-scale solid organs remains limited by the inability to establish dense, functional vascular networks capable of sustaining metabolically active tissues. This focused review summarizes the complexities involved in generating physiological vasculature and highlights progress in several approaches developed over the past two decades. We discuss progress across several core technology categories, including organoid-based and microfluidic-based platforms to model the vasculatures, as well as the techniques feasible to construct an organ-scale tissue, including recellularization of decellularized organ scaffolds, and bottom-up biofabrication approaches for complex 3D vasculature and high-cell density compatibility. By synthesizing insights from these complementary approaches, we highlight emerging design principles for constructing hierarchical and functional vascular networks. Finally, we outline a forward-looking roadmap toward scalable vascularization strategies that may enable the realization of biofabricated, functional human organs in the coming decade.
Conventional brain stimulators primarily rely on implantable batteries, necessitating repeated replacement surgeries. Ultrasound-driven stimulators offer a promising wireless alternative, yet existing systems are predominantly extracranial and face limitations in stability and efficiency. Here, we fabricated a miniaturized, implantable ultrasound-driven intracranial brain stimulator (UIBS), achieving stable and efficient neuromodulation. The UIBS was developed by integrating a flexible composite structure consisting of PVDF-TrFE and a flexible acoustic matching layer with a rectifier circuit embedded in a PEEK structure. Additionally, transcranial ultrasound transmission was optimized through numerical simulations and experimental validation. Electrical output performance, the electrolysis-defined safety window, and neuromodulation efficacy as well as biocompatibility following UIBS implantation into the rat primary somatosensory cortex were systematically assessed. The optimal transcranial ultrasound frequency was determined to be 1.5 MHz. Driven by transcranial ultrasound at 2 MPa, the UIBS generated a rectified output voltage exceeding 1.3 V, with a safe electrolysis duration exceeding 10 seconds at 100 Hz. Furthermore, in vivo experiments demonstrated that under ultrasound driving, the device can be stably implanted and reliably evoke neural activity in the primary somatosensory cortex, while maintaining good biosafety. This work presents a novel and miniaturized UIBS, enabling effective intracranial energy harvesting and precise neuromodulation, addressing key constraints of battery-dependent and extracranial devices.