共找到 20 条结果
暂无摘要（点击查看详情）
Background/purpose Breast cancer is among the most prevalent malignancies treated at the Liga Nacional Contra el Cáncer (LNCC) in Guatemala, representing a significant proportion of annual radiotherapy cases. Access to high-quality, standardized treatment planning in resource-constrained settings remains a critical challenge. This study evaluates the dosimetric performance of knowledge-based planning (KBP) models adapted from Washington University (WashU) in St. Louis for breast and chest wall radiotherapy at LNCC, validated against a retrospective 2025 clinical cohort, and benchmarked against the ASTRO 2026 Practical Radiation Oncology guidelines. Materials and methods A retrospective analysis of 84 treatment plans (40 left, 44 right) for whole-breast or chest-wall treatment with regional nodal involvement was performed. All patients were treated using volumetric modulated arc therapy (VMAT) under a moderate hypofractionation scheme (40.05 Gy in 15 fractions). KBP models were developed during 2022-2024 using Eclipse V18.0 (Varian Medical Systems, Palo Alto, CA) RapidPlanTM, originally built at Washington University, and augmented with 194 left-breast and 103 right-breast cases from LNCC. Model validity was confirmed with Varian's model analytics tool. Dosimetric metrics for the planning target volume (PTV) and organs at risk (OARs) were extracted using a custom ESAPI (the OWASP enterprise security application programming interface) application and compared against ASTRO 2026 Table 3 benchmarks, categorized as recommended (green), acceptable (yellow), or unacceptable (red). Results PTV coverage was adequate, with an average V95% of 97.3% ± 1.8%; V90% of 99.7% ± 0.4 (right), and average V95% of 96.6%±3.8%; V90% of 99.0%, ± 2.8% (left). Most plans met ASTRO's recommended range. The heart mean dose was well-controlled, with median values of 2.4 Gy (right) and 4.2 Gy (left). Ipsilateral lung V18Gy showed a median of 18.6% (right) and 17.7% (left), and V10Gy of 33.3% (right) and 31.6% (left), both within acceptable ranges. Spinal cord D0.035cc had a median of 8.3 Gy (right) and 10.1 Gy (left), well below neurological tolerance thresholds. Contralateral breast D10% had median doses of 2.6 Gy (right) and 2.9 Gy (left), with ranges of 1.7-3.1 Gy and 2.2-5.4 Gy, respectively. KBP model analytics validation confirmed institutional model statistics fell within acceptable quality benchmarks across all evaluated structures. Conclusion KBP models developed at a high-income institution and iteratively refined with local data can be successfully deployed for breast and chest wall radiotherapy in a resource-constrained low- and middle-income country (LMIC) setting, achieving dosimetric outcomes consistent with ASTRO 2026 guidelines. The temporal separation between model training (2022-2024) and retrospective validation (2025) further confirms the models' robustness and generalizability. This approach supports standardized, high-quality treatment planning at scale, contributing to more equitable access to radiotherapy for breast cancer patients.
Heavy-duty diesel vehicles remain an important in-use source of atmospheric NOx, yet long-duration characterization of real-world emissions is constrained by the cost of Portable Emission Measurement Systems (PEMS) and by the irregular structure of Onboard Diagnostics (OBD) telematics. Using 13 months of 1 Hz telematics data from 502 China VI heavy-duty diesel vehicles, covering approximately 1.7 million trips, this study developed a Short-Trip Combination Method (STCM) to reconstruct a screening-oriented estimate of the 90th-percentile Moving Average Window (MAW) specific NOx emission indicator for hot-running operation. STCM segments thermally stabilized operation into short trips, classifies trips by driving mode, reconstructs regulation-constrained synthetic cycles through Monte Carlo resampling, and then calculates the MAW-based NOx indicator. The framework was benchmarked against 15 PEMS tests on four representative vehicles and further compared with a simple whole-trip averaging baseline. A 51-h evaluation window and 200 Monte Carlo iterations provided stable estimates. Median STCM estimates fell within the range of repeated PEMS measurements, with vehicle-level absolute errors of 0.11-0.182 g/kWh, whereas the supplementary baseline comparison showed lower agreement for whole-trip averaging. These results indicate that irregular long-duration OBD data can be converted into environmentally relevant hot-running NOx indicators that recover persistent elevated-emission behavior under real-world operation. Rather than replacing regulatory PEMS testing, the proposed framework provides a practical basis for continuous fleet-scale screening and prioritization of vehicles or operating periods requiring confirmatory inspection.
The development of tidal stream energy sites is constrained by numerous practical, technical, and accessible constraints, including changes in the flow caused by the presence of the tidal farm. Large and complex sites are typically developed incrementally and may involve multiple developers. This regional modelling case study of the Pentland Firth, widely regarded as one of the most significant global locations for tidal energy extraction, investigates these dynamics. This study examines scenarios for the incremental development of the Pentland Firth, incorporating assumptions regarding tidal farm design. The analysis considers a range of configurations, including variations in turbine density and the incorporation of shipping lanes within designated lease areas. The study finds that there are interactions between individually developed tidal farms of the site, but they are moderate with the power in a given farm unlikely to vary by more than 20% (based on a positive interaction), as a result of the development of other farms in other parts of the Pentland Firth. To minimise such array interactions, it is recommended that site leasing be based on the allowable thrust applied to the flow rather than on projected power generation. Furthermore, the findings suggest that the maximum power generated from turbines in the Pentland Firth, averaged over time, is unlikely to exceed approximately 1 GW, broadly consistent with most estimates in the literature.
Southeast Asia's international rivers sustain the livelihoods of hundreds of millions of people and represent globally important biodiversity hotspots and ecologically sensitive regions. The scarcity of hydrological station data has constrained our understanding of long-term hydrological evolution, water cycle dynamics, and hydrological modelling in these basins. Here, we present a compilation of historical daily records of streamflow (87 stations), sediment concentration (40 stations), and water level (118 stations) in the upper reaches of the Irrawaddy, Salween, Mekong, and Red River basins for the period 1958-1987. Based on these records, we derived 74 hydrological indices. For streamflow, data were available from 12 stations in the Irrawaddy basin (mean record length 23 years), 13 in the Salween basin (18.8 years), 34 in the Mekong basin (21.1 years), and 28 in the Red River basin (23.3 years). Water level records covered 14 Irrawaddy stations (mean 20.92 years), 20 Salween stations (15.57 years), 48 Mekong stations (18.75 years), and 35 Red River stations (19.68 years). Sediment concentration data were available for 5 Irrawaddy stations (mean 13 years), 7 Salween stations (15.85 years), 16 Mekong stations (14.37 years), and 12 Red River stations (17.25 years). Overall, water level stations are the most numerous across the four basins, whereas sediment concentration stations are the fewest. The derived hydrological indices are crucial for elucidating the historical hydrological evolution of the upper Irrawaddy, Salween, Mekong, and Red River basins. In addition, these data provide valuable support for interdisciplinary studies of transboundary river environments, hydrology, ecology, and natural flow reconstruction, and for calibrating and validating numerical models. This dataset fills a key gap in large-sample global hydrological studies by improving the representation of this previously underrepresented region.
Recent advances in genetic engineering and in vivo reprogramming have opened transformative possibilities for controlling cell fate in tissue repair and regeneration. However, clinical translation remains constrained by the limited predictive value of animal models and traditional in vitro systems, which often fail to fully recapitulate human responses, including the physiological consequences of genetic manipulations. Emerging microphysiological systems, exemplified by three-dimensional organoids and organs-on-chips (OoCs) systems, help bridge this gap by recreating key aspects of human physiology while enabling precise bioengineering of the niche to modulate cell fate decisions and plasticity. Organoids derived from induced pluripotent stem cells, adult stem cells, primary tissues, or directly reprogrammed cells preserve the patient-specific genetic background, facilitating mechanistic studies of development and disease and the evaluation of gene correction and reprogramming strategies in a human-relevant context. Complementarily, OoC platforms provide regulated perfusion, tissue vascularization, mechanical forces, molecular gradients, and immune cell integration to promote tissue maturation, functional readouts, and quantitative assessment of therapeutic responses that are difficult to achieve in static cultures. In this review, we discuss how organoids and OoC-based platforms are being leveraged to study and enhance cell fate reprogramming, repair, and regeneration across multiple tissues. We highlight recent reports where these systems informed the design, optimization, and safety evaluation of gene and cell therapies. Finally, we outline current limitations, including scalability, standardization, and biomaterial constraints, and propose future directions for integrating organoids, OoC, and gene-modulation technologies to enable more predictive, personalized, and clinically translatable regenerative medicine.
Chip-scale transition metal dichalcogenide (TMDC) waveguides offer giant material nonlinearity for integrated photonics. However, research has predominantly focused on maximizing conversion efficiency, leaving the polarization mechanisms of the generated nonlinear signal largely unexplored. Here, we establish a comprehensive framework for engineering the polarization of second-harmonic generation (SHG) within 3R-MoS2 planar waveguides. By synergizing polarization-resolved measurements with theoretical modeling, we reveal that SHG polarization is governed by guided-mode interactions constrained by waveguide geometry and crystal symmetry, and continuously reshaped during propagation. We demonstrate that thickness-dependent modal confinement and in-plane crystal symmetry provide robust static control, while propagation length serves as a dynamic tuning knob for tailoring the nonlinear output. Our findings establish a deterministic approach for on-chip polarization engineering, opening new avenues for reconfigurable nonlinear light sources and quantum photonic circuits.
Drug-induced reproductive toxicity is a critical concern in drug safety evaluation, whereas conventional assessment methods are often constrained by high costs and long experimental cycles. In this study, a machine learning-based predictive model for reproductive toxicity was developed and integrated with data from the FDA Adverse Event Reporting System (FAERS), network toxicology analysis, molecular docking, and molecular dynamics simulation to systematically evaluate the post-marketing reproductive toxicity risk of drugs and explore their potential mechanisms. Among the evaluated machine learning algorithms, LightGBM demonstrated the best overall performance, achieving an F1-score of 0.854, a ROC-AUC of 0.933, a PR-AUC of 0.931, and an MCC of 0.705 on the independent test set, with robust generalization confirmed by ten-fold cross-validation. Among drugs approved between 2015 and 2024, 72 were predicted to have a high risk of reproductive toxicity. FAERS-based signal comparison showed that 55 of these drugs (76.39%) were associated with reproductive toxicity-related adverse event reports, indicating consistency between model predictions and FAERS-reported reproductive toxicity-related adverse events. Network toxicology analysis identified 12 key targets, including ESR1, IGF1, and AKT1, that may be involved in reproductive toxicity. Molecular docking showed that drugs with high predicted reproductive toxicity risk could bind effectively to multiple toxicity-related targets, while molecular dynamics simulations confirmed stable interactions between selected drugs and ESR1, mainly through hydrogen-bonding and hydrophobic interactions. Favorable binding free energies further supported their potential multi-target effects. Overall, this integrated strategy combining predictive modeling with FAERS-based signal comparison provides a useful framework for drug safety evaluation and mechanistic investigation of reproductive toxicity.
Emergency departments in low- and middle-income settings face rising patient volumes, overcrowding, and constrained medical resources, making accurate early triage essential to prioritize lifesaving care while avoiding unnecessary use of resuscitation capacity. Although the 3-tier color-coded All India Institute of Medical Sciences triage protocol (red/yellow/green) has shown strong prognostic validity when applied by physicians, evidence on its real-world diagnostic accuracy when implemented by nurses in Indian tertiary-care centers remains limited. This retrospective cross-sectional study evaluated nurse-led triage using a modified All India Institute of Medical Sciences triage protocol in the Department of Emergency Medicine at All India Institute of Medical Sciences, Raipur (annual census, ∼54,000), including adult trauma and nontrauma presentations from June to August 2025. Using systematic random sampling (every fifth patient), 2584 records were analyzed after excluding brought-dead cases and records with incomplete documentation (n = 89) or missing outcomes (n = 43). Nurse-assigned triage served as the index test and was compared with a blinded expert physician reference standard (2 independent emergency physicians with adjudication by a senior reviewer; interrater quadratic-weighted kappa = 0.61). Nurses achieved 85.3% exact agreement (95% CI, 83.9-86.5) with good overall agreement (quadratic-weighted kappa = 0.78); most discordances were 1-step (14.3%) and severe mismatches were rare (0.4%). Undertriage (12%) substantially exceeded overtriage (3%). For identifying red cases (expert red, n = 751), the sensitivity was 0.79 and the specificity was 0.97, yielding 92% accuracy for red vs not red; 21.8% of true red patients were undertriaged (1.5% to green). Mortality increased with higher acuity, with no deaths among green by either rater; mistriage was not significantly associated with discharge mortality (relative risk, 0.52; 95% CI, 0.22-1.23; P = .113). In multivariable analysis, trauma (odds ratio, 4.41; P < .001) and alert presentation (odds ratio, 1.92; P < .01) independently predicted incorrect triage. Nurse-led modified All India Institute of Medical Sciences triage protocol demonstrated high reliability and specificity but a clinically important undertriage tendency, particularly in trauma and alert patients, supporting targeted training on injury kinematics and mitigation of ambulatory bias, alongside system aids (eg, checklists/electronic prompts) to improve safety.
Squamous cell carcinoma (SCC) is a malignant epithelial neoplasm commonly affecting the skin and oral cavity of dogs, whereas laryngeal involvement is considered rare. Neoplasms arising in the larynx may cause severe upper airway obstruction and present diagnostic and therapeutic challenges due to the anatomical and functional constraints of this region. An 11-year-old neutered male mixed-breed dog was evaluated for a one-month history of progressive upper airway obstruction characterized by dyspnea, tachypnea, and dysphagia. Clinical examination revealed a solitary mass protruding into the laryngeal lumen in the arytenoid region. Surgical excision was performed, and intraoperative frozen section evaluation indicated compromised surgical margins. Definitive histopathology confirmed an invasive SCC. Adjunct electrochemotherapy was applied following identification of compromised surgical margins, and the dog showed favorable short-term clinical recovery following surgery. No evidence of recurrence or metastasis was observed during a three-month follow-up period. This case highlights the clinical relevance of laryngeal SCC in dogs and emphasizes the importance of thorough clinical examination and early detection, as well as the integration of clinical evaluation, histopathology, and intraoperative margin assessment in the management of upper airway neoplasms. The combined use of surgical excision, frozen section analysis, and adjunct electrochemotherapy may be considered a potential therapeutic approach in anatomically constrained regions where complete tumor removal is limited.
The benefit of long-term albumin (LTA) in improving survival and reducing complications in patients with cirrhosis and ascites is not consistently observed across studies, possibly reflecting differences in patient populations and treatment regimens. This study aimed to determine whether baseline serum albumin (SA) levels can predict which patients are most likely to benefit from LTA therapy. A post hoc analysis of the ANSWER trial was performed in 431 patients randomized to receive standard medical treatment (SMT) alone or SMT plus human albumin (SMT + HA). The interaction between baseline SA and LTA was investigated using competing-risk survival analysis. The primary endpoint was 18-month survival. Secondary endpoints included the incidence of cirrhosis-related complications and hospitalizations. A significant treatment-by-albumin non-linear interaction was found (p = 0.010), indicating heterogeneity of treatment effect across baseline SA levels with the upper bound of the region of statistically demonstrable benefit occurring at approximately 3.2 g/dL (sHR 0.53, 95% CI 0.28-0.99). In patients with SA ≤ 3.2 g/dL, 18-month survival was significantly higher in the SMT + HA group compared with SMT alone (HR 0.47, 95% CI 0.29-0.77; p = 0.0021). No significant survival difference could be demonstrated in patients with SA > 3.2 g/dL (HR 1.04, 95% CI 0.41-2.63; p = 0.93). Regardless of baseline SA levels, LTA was associated with improved ascites control and reduced rates of complications and hospitalizations. LTA provides survival and morbidity benefits in patients with mild-to-moderate hypoalbuminemia, whereas in patients with normal SA levels, its benefit appears mainly limited to morbidity reduction. Baseline SA may therefore help in prioritizing LTA therapy when resources are constrained.
Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes such as cell division and intracellular transport. However, this task is highly challenging due to the fine, densely packed, and intertwined nature of these structures. Imaging limitations-noise, low contrast, and uneven fluorescence-further complicate analysis. While deep learning has advanced segmentation of large, well-defined biological structures, its performance often degrades under such adverse conditions. Additional challenges include obtaining precise annotations for curvilinear structures and managing severe class imbalance during training. We introduce a novel noise-adaptive attention mechanism that extends the Squeeze-and-Excitation (SE) module to dynamically adjust to varying noise levels. Integrated into a U-Net decoder with residual encoder blocks, this yields ASE_Res_UNet, a lightweight yet high-performance model. To address annotation challenges, we developed a synthetic dataset generation strategy that ensures accurate annotations of fine filaments in noisy images, producing a synthetic dataset with two difficulty levels for segmentation benchmarking. We systematically evaluated loss functions and metrics to mitigate class imbalance, ensuring robust performance assessment. ASE_Res_UNet effectively segmented microtubules in noisy synthetic images, outperforming its ablated variants. It also demonstrated superior segmentation compared to models with alternative attention mechanisms or distinct architectures, while requiring fewer parameters, making it efficient for resource-constrained environments. Evaluation on a newly curated real microscopy dataset and a recently reannotated dataset highlighted ASE_Res_UNet's effectiveness in segmenting microtubules beyond synthetic images. For these datasets, ASE_Res_UNet was competitive with a recent synthetic data-driven approach that shares two cytoskeleton pretrained models. Importantly, ASE_Res_UNet showed strong transferability to other curvilinear structures (blood vessels and nerves) across diverse imaging conditions. This work advances microtubule segmentation through three key contributions: (1) Providing two benchmark datasets (synthetic and real), addressing a critical gap in standardised evaluation resources for this task; (2) Introducing ASE_Res_UNet, a lightweight yet robust model combining noise-adaptive attention with residual learning; (3) Validating competitive performance across synthetic and real microscopy data. Additionally, we demonstrated the robustness and versatility of the proposed architecture across diverse curvilinear segmentation tasks, showcasing potential for broader applications in biological research and medical diagnosis.
The hydrostibination of alkenes represents a largely underdeveloped transformation, owing to the intrinsic lability of the required Sb─H reagents. We now show that an Sb─H bond is not needed. The structurally constrained, amidophenolato-pyridyl supported T-shaped stibenium(III) ion undergoes anti-Markovnikov hydrostibination of a broad range of alkenes in excellent yields. Spectroscopic and computational analyses reveal a polarizable, redox-confused Sb-π system in the cation, whereas its reactivity follows closed-shell ionic pathways characteristic of a Lewis-acidic Sb(III) center. Mechanistic studies support element-ligand cooperativity (ELC) with the hydride equivalent for hydrostibination originating from the ligand scaffold after substrate activation at antimony. The resulting stiba-alkanes can be transformed quantitatively into haloalkanes. This work establishes a viable strategy for hydroelementation with heavy p-block elements while circumventing weak and labile E─H bonds.
ConspectusPlatinum (Pt)-based anticancer drugs have been a cornerstone of chemotherapy for decades, yet their clinical application remains constrained by dose-limiting systemic toxicity and drug resistance. In this Account, we summarize our systematic efforts to address these challenges through two complementary strategies: 1) functionalization of Pt(IV) prodrugs and 2) spatially controlled targeted delivery. The kinetic inertness and octahedral geometry of Pt(IV) complexes offer a versatile platform for axial functionalization, allowing the integration of diverse bioactive ligands that are released upon intracellular reduction. Exploiting this feature, we have developed multifunctional Pt(IV) prodrugs that co-target DNA damage repair and apoptotic pathways, rewire cholesterol and energy metabolism, induce nonapoptotic cell death including PANoptosis and autophagy-associated death, and epigenetically silence resistance-associated gene networks via chromatin compaction. To engage the tumor immune microenvironment, we have incorporated immunomodulators─including STING agonists, TREM2/CD33 inhibitors, and STAT3 blockers─to amplify innate and adaptive antitumor immunity. Furthermore, we have developed radiotherapy-responsive Pt(IV) prodrugs that undergo rapid, X-ray-triggered reduction mediated by hydrated electrons, enabling spatiotemporally precise drug activation with markedly attenuated systemic toxicity. This strategy is currently advancing toward clinical translation through IND-enabling studies. In parallel, we have established targeted delivery platforms to improve the spatial precision of Pt agents. Mitochondria-targeted complexes redirect cytotoxicity to an organelle lacking efficient DNA repair, disrupting bioenergetics and triggering intrinsic apoptosis. At the tissue level, biotin-mediated targeting exploits overexpressed vitamin transporters for tumor-selective accumulation, while Pt(IV)-antibody conjugates (Pt-ADCs) achieve antigen-specific delivery, upregulate tumor MHC-I expression, expand TCR clonotypes, and synergize with PD-1 blockade. Additionally, a stimuli-responsive in situ self-assembly strategy enables enzyme-triggered nanostructure formation and intracellular disassembly for enhanced tumor accumulation and burst drug release. An immunocompetent patient-derived organoid platform has been established to screen these agents in a clinically relevant setting. The integration of multifunctional modulation, targeted delivery, and externally controlled activation within single Pt-based systems creates a synergistic framework that simultaneously addresses resistance and toxicity. Moving forward, our research will focus on optimizing pharmaceutical properties, advancing radiotherapy-responsive Pt(IV) prodrugs and Pt-ADCs toward clinical evaluation, and refining predictive screening platforms. These programmable Pt therapeutics hold considerable promise for delivering safer and more effective precision chemotherapy to cancer patients.
An augmented virtuality framework is presented in which the physical scene is admitted only through developer-defined geometric apertures, while all other pixels are rendered virtually. The scene initialises as a black field and uses surface-projected, overlay-style compositing so that the camera stream is visible only on circular or square meshes registered as projection surfaces. Tracking origin is configured to minimise unintended recentring, and the same method can operate either as a minimal black scene or within an optional three-dimensional environment. Main features of the framework are as follows: deterministic compositing that binds real imagery to user-defined meshes and prevents leakage outside apertures. stable alignment between virtual geometry and the physical workspace during head motion achieved through standard XR configuration. a flexible scene recipe that supports circular or square apertures and optional contextual environments without altering projection logic. The framework is intended for sensory and consumer studies that require real product interaction under controlled context and generalises to training, human factors, and rehabilitation scenarios requiring constrained visibility of the real world.
Energy landscapes provide a useful lens for understanding multistability and state transitions in self-organizing systems, but systematic characterization of the energy landscapes for coupled oscillator networks remains less well developed. Here, we study a frustrated Stuart-Landau oscillator network on a 2D toroidal lattice with competing local coupling and global frustration and characterize how its macroscopic states and noise-driven transitions reorganize as the frustration strength is varied. We combine a mode-based, phase-decoupled approximation with homotopy continuation and track representative families of equilibria from the approximation to the full model. In singular cases where the leading XY-Hamiltonian phase interaction yields non-isolated critical points, we impose a second-order phase equilibrium condition and solve it in a constrained-solvability sense to ensure that continuation is well posed. Numerical continuation shows partial selectivity of this homotopy, in which lower-energy initializations tend to continue to similarly lower-energy, lower-index equilibria in the full system. Across frustration regimes, continuation shows how approximate equilibria split and reorder by energy and index; at intermediate frustration, extensive runs reveal multistability between an isolated global minimum and multiple 1D troughs contained within the edges of a multigraph. Guided by the resulting landscape-level picture, simulations demonstrate distinct noise-dependent synergetic phenomena, including noise-induced synchronization, noise-induced desynchronization, and persistent switching among coexisting macrostates. Stationary transition kinetics exhibit both Arrhenius-Kramers-like (activated) and diffusion-limited scaling with respect to noise. These results support a coupled-oscillator-based framework for analyzing the energy landscape of multivariate time series, with potential applications in neuroscience, physiology, and beyond.
China achieved World Health Organization certification for malaria elimination in 2021; however, the risk of local retransmission from imported malaria remains a primary challenge in the post-elimination era. While international trade is a critical driver of importation risk, current risk assessments are constrained by the lack of granular cross-border population mobility data. This study introduces service trade volume as a proxy for population mobility. By integrating global malaria epidemiology, socioeconomic factors, and geographic resistance, an enhanced gravity model was developed to stratify global malaria importation risks. The findings revealed that Plasmodium falciparum importation risk exhibited pronounced geographic clustering, predominantly in sub-Saharan Africa. Conversely, Plasmodium vivax importation showed a distinct "connectivity-driven" pattern. Notably, low-endemicity countries geographically adjacent to China or sharing intensive trade relations (such as Republic of Korea, Thailand, and Vietnam) present substantial cryptic importation pressures, identifying them as pivotal surveillance targets in the post-elimination era. The risk stratification matrix provides a scientific framework for tailoring surveillance strategies. For "high-endemicity, high-mobility" regions (such as specific African nations), priorities should focus on strengthening port-of-entry screening and post-arrival follow-up. For "low-endemicity, high-mobility" regions, heightened vigilance is required against cryptic importations driven by frequent commercial and economic exchanges. Public health strategies must move beyond analyses based solely on geographic proximity and incorporate economic connectivity metrics into active surveillance frameworks.
The speed of insulin therapy remains fundamentally constrained by the self-association of insulin into hexamers. Here, a materials-based strategy is introduced to stabilize HALQ, a monomeric insulin analog, using a non-interacting inulin-derived excipient (BN-Inu). BN-Inu markedly mitigates aggregation and maintains HALQ stability for 96 h under stress and for at least 30 days at room temperature. In a porcine model of diabetes, monomeric HALQ exhibits significantly accelerated absorption and a shorter duration of action than the ultrarapid insulin aspart Fiasp. This "fast-on, fast-off" profile is consistent with faster clearance from the subcutaneous depot, more closely synchronizes with endogenous prandial insulin physiology. Addition of clinically used absorption enhancers further accelerates its pharmacokinetic profile, producing a faster time-to-peak and reduced exposure relative to ultrarapid insulin lispro Lyumjev in this animal model. Furthermore, translation to human physiology was evaluated through pharmacokinetic modeling, which predicts that HALQ could reduce time-to-peak from 60 to 39 min and shorten duration of action from 143 to 84 min in humans. These simulations suggest the potential utility of achieving a step-change in the speed of insulin therapy. These findings demonstrate that monomer-stabilizing excipients enable next-generation ultrafast insulin formulations with the potential to improve glycemic control in diabetes.
Although tree imagery in projective drawing tests is a promising nonverbal tool for screening mental disorders, its clinical utility remains constrained by inconsistent predictor selection. To address this gap, the present systematic review and meta-analysis synthesizes the characteristics of tree imagery linked to mental disorders and evaluates their predictive efficacy. Following the PRISMA guidelines, we analyzed 42 studies involving 8552 participants from English and Chinese databases published between 1948 and 2024. The results showed that 24 specific characteristics significantly predicted mental disorders (p < 0.05), which were classified into five distinct categories: blackened out (e.g., blackened tree, odds ratio [OR] = 2.01), scribbled lines (e.g., weak lines, OR = 2.82), oddly shaped (e.g., flattened crown, OR = 3.10), no vitality (e.g., very small tree, OR = 3.93), and overly simple (e.g., simplified drawing, OR = 7.07). Furthermore, subgroup analyses indicated that features such as "blackened tree" (OR = 1.71), "no motion" (OR = 3.34), and "excessive separation" (OR = 2.77) were significantly associated with affective disorders, whereas the presence of "roots" (OR = 4.89) was uniquely associated with the thought-disorder subgroup. Ultimately, tree imagery may offer a valuable nonverbal, adjunctive approach to screening for mental disorders, offering several statistically supported indicators that may effectively complement traditional assessment tools.