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Hydrogen-bonded organic frameworks (HOFs) have emerged as promising materials for biomedical applications owing to their metal-free biocompatibility and recyclability. Notably, most HOFs are synthesized and utilized in organic solvents, limiting their biomedical translation. Although water is a biologically compatible alternative, it competes for hydrogen bonding and disrupts interactions between building blocks, making the construction of stable aqueous HOFs challenging. Inspired by the DNA base pairing structure, the first nucleoside-based HOF (N-HOF-1) was developed using a multi-hydrogen bonding strategy. This framework is synthesized entirely in water by simply mixing 2-amino-2'-fluoro-2'-deoxyadenosine (2FA) and cyanuric acid (CA), enabling grade production while maintaining stability under physiological conditions. Microcrystal electron diffraction (MicroED) and single-crystal X-ray diffraction (SCXRD) studies revealed the confinement of M-shaped water clusters within the channels of N-HOF-1, mimicking DNA hydration and preserving the HOF architecture. Notably, the porous and positively charged properties of N-HOF-1 enable interaction with bacteria to form the bacteria-nanoparticle biohybrid systems. Leveraging the intrinsic bioactivity of nucleoside building blocks, this system enhances engineered bacterial colonization in the periodontium, periodontal tissue regeneration, and lymphoma therapy. These findings highlighted the potential of nucleosides as versatile building blocks for hydrophilically stable HOFs, offering new possibilities for their biomedical applications.

Interstitial lung disease (ILD) is a serious irreversible, often progressive, lung condition that can lead to respiratory failure and early death. Indian data on epidemiology of the disease is scarce. To better understand the nation-wide burden, population characteristics and treatment outcomes, and capacity building of clinicians for management of patients with ILDs, ICMR's Network of Pulmonary Fibrosis (INPF) was established. Objective: To describe the rationale, protocol, and current status of INPF. The network, consisting of 23 centres across the country, was formally launched in August 2022. Governed by the Indian Council of Medical Research (ICMR) and its task force (TF) committee, INPF has been recruiting all new and previously diagnosed adult patients (age >18 years) with ILDs. The diagnosis and sub classification of ILD was based on multi-disciplinary team discussion (MDD). The data is secured in the online database incorporated in the INPF website. Progress of the network is continuously monitored by the investigators at the centres and by the TF at the ICMR. As on February 2026, 11,544 have been enrolled in INPF. Connective disease associated-ILD (CTD-ILD) was the most common ILD constituting 28.46% (3,286) of the patients. Currently, patients are being enrolled for four proposed sub-studies with satisfactory progress. Four capacity building sessions has been conducted. INPF is one of the largest ILD registries in the world. It also provides pulmonologists a platform to conduct research in ILD and better equip themselves to manage patients.

Social media has become an increasingly prevalent platform for exchanging health information, facilitating professional networking, promoting education, and fostering public engagement. For surgeons, its benefits-rapid dissemination of knowledge, community building, conference amplification, advocacy, and recruitment-coexist with heightened ethical risks, including breaches of confidentiality, blurred professional boundaries, misinformation, conflicts of interest, and inequities in access. This SAGES Ethics Committee white paper provides an ethics-focused overview of surgeon social media use and offers practical recommendations aligned with core bioethical principles, incorporating previous work from the SAGES Social Media Committee, the SAGES Facebook Taskforce, and the SAGES Ethics Committee. We synthesize existing professional guidance and the peer-reviewed literature on social media in healthcare and surgery to identify recurring ethical dilemmas across stakeholder groups (surgeons, patients, institutions, and society). We organize these issues using the four principles of biomedical ethics-autonomy, beneficence, non-maleficence, and justice-and translate them into actionable standards for professional conduct, content stewardship, and institutional oversight. Key ethical domains include the following: (1) professionalism and identity management in blended personal/professional spaces; (2) confidentiality and the Health Insurance Portability and Accountability Act of 1996 (HIPAA)-informed safeguards when sharing clinical images, videos, and case discussions; (3) disclosure and conflict-of-interest management in self-promotion, marketing, endorsements, and "non-evidence-based" content; (4) boundaries in patient interaction, emphasizing that social media should not be used for direct patient-provider communication in lieu of secure, trackable clinical platforms; (5) respect for patient privacy, including a general expectation that clinicians should not search patients' social media absent compelling, disclosure-supported exceptions (e.g., emergent identification needs); (6) consent standards for recording or posting media involving patients or clinicians; (7) equity considerations, recognizing that reliance on social platforms can worsen disparities for individuals lacking access or digital health literacy; and (8) societal-level implications such as clinical trial recruitment, crowdsourcing, misinformation correction, wellness harms from excessive use, and emerging risks/opportunities from artificial intelligence (AI)-enabled amplification and data mining. Ethical social media engagement by surgeons is feasible and often beneficial when guided by transparency, accuracy, confidentiality protection, boundary maintenance, and equity. We recommend clear disclosures, separation of personal/professional accounts when feasible, institutional and society-level monitoring frameworks for official messaging, strict consent and de-identification standards for clinical content, avoidance of social media as a clinical communication channel, and ongoing review of AI-driven changes to platform dynamics and privacy risk.

The replacement of the oxygen evolution reaction (OER) with biomass-derived molecule oxidation offers a promising strategy to reduce the energy demand of alkaline water electrolysis while allowing the simultaneous production of value-added chemicals. However, the practical implementation of such coupled systems remains limited by the scarcity of cathode materials that are selective toward the hydrogen evolution reaction (HER) in the presence of reactive organic substrates. In this work, we present the synthesis and electrocatalytic performance of a noble-metal-free and scalable MoS2 nanosheet@graphene nanoplatelet (MoS2 Nsh@GNP) composite designed for effective hydrogen production in mild-alkaline media in the presence of hydroxymethylfurfural (HMF) as a biomass-derived organic building block molecule. The hexagonal 2H-MoS2 nanosheet morphology with maximized accessible catalytic edge sites, combined with the enhanced dispersion and 3D-conductivity provided by graphene scaffold, results in a notable improvement of charge transport, as demonstrated by the observed overpotentials of -0.32 V at 10 mA cm-2 and -0.49 V at 100 mA cm-2 in 0.1 M NaOH + 1 M Na2SO4 (pH ∼13). Systematic electrochemical experiments, coupled with microgas chromatography and 1H NMR byproduct analyses, reveal that the HER selectivity is preserved up to 30 mM HMF in the electrolyte. Importantly, stable operation at pH 13, intentionally selected to avoid HMF instability at pH 14, demonstrates the suitability of this cathode material for membraneless biomass-assisted alkaline electrolysis.

Urea electrolysis plays a key role in various urea waste valorization processes. In this regard, the complex six-electron transfer process, urea oxidation reaction, is the key to achieving maximum efficiency. In this study, we developed multilayered α-Ni-(OH)2 sheets through a sonochemical approach. We used Fe3+ to dope the α-Ni-(OH)2 sheets in three different compositions. The synthesized catalysts were analyzed by using XRD, SEM, EDX, FTIR, and XPS. Using EDX and XPS, successful doping of iron was confirmed. The electrocatalytic activities were characterized by CV, LSV, EIS, and CA techniques. Through CV analysis, it was identified that Fe3+ did not directly participate in the electrochemical reaction; rather, due to high Lewis acidity, it was modulating the electronic environment of Ni2+ ions. Iron doping induced a reduction in the onset potential and synergistically increased the catalytic current by promoting a higher number of active sites for urea adsorption. Tafel analysis concluded that the improved reaction kinetics was due to iron incorporation. Using Nyquist and Bode plots, it was identified that iron doping promoted CO2 production as RDS. Therefore, catalyst poisoning due to prolonged adsorption of CO2 was diminished, and subsequently, catalyst stability was increased. Overall, while Fe3+ doping has proved to be a significant method to enhance catalytic activity, careful optimization of concentration is required to build a state-of-the-art catalytic architecture for urea waste valorization.

Ohio has been severely affected by the opioid epidemic for more than a decade, leading to the development of diversion and deflection programs that seek to intervene with individuals experiencing substance use disorder in the community. The Comprehensive Opioid, Stimulant, and Substance Use Program provided funding to develop or enhance 9 first responder-led diversion/deflection efforts across the state of Ohio and examine their operations and impact on client outcomes from 2021 to 2024. Although heterogeneously implemented, each of the 9 funded deflection teams engaged in overdose response or proactive outreach, targeting people with substance use disorder to connect them to community-based treatment resources, overdose prevention materials, and other supports based on the needs of the individual. Demographics for referrals across the sites, number of referrals/unique individuals recorded per team, deflection team activities (ie, contact attempts, successful contact rates, overdose prevention material distribution), and clients' proximal outcomes of connection to treatment are reported. In addition, successful rates of contact and connection to treatment were examined across demographic groups. Less than 25% of all teams had any significant differences in rates of contact or connections to treatment between demographic groups. Nearly 80% of the teams showed significant differences in mean number of contact attempts between successful and nonsuccessful contacts. This multisite evaluation contributes to a small but growing body of research on deflection programs. It emphasizes 2 proximal outcomes that are directly tied to team activities. It also builds on past research by examining how client demographics and team activities (ie, contact attempts) may influence client outcomes.

The association between armed conflict and intimate partner violence (IPV) is well established. However, the mechanisms or drivers of this relationship are less well understood. This review provides a systematic synthesis of published literature on the factors driving the association between violence in the public and private spheres. Five databases (Web of Science, EMBASE, CINAHL, PsycINFO and PubMed) were systematically searched to identify all studies examining potential drivers. Inclusion criteria specified that studies should be based on adult samples, should measure or analyse the impact of conflict exposure, and should provide some insight into the drivers of the association between armed conflict and IPV, rather than only documenting the association. A total of 49 studies (25 qualitative and 24 quantitative) met the inclusion criteria. Identified drivers included individual, relational and structural factors. Among the most empirically supported drivers were conflict-related trauma and post-traumatic stress disorder (PTSD), stress associated with the economic effects of conflict and changes to gender roles and norms in the post-conflict setting. The intersection of these factors, particularly gender roles and economic factors, also emerged as a significant dynamic across multiple studies. The findings highlight the importance of integrating gender considerations, including IPV prevention and response, into humanitarian programming. There is a need for further research and theory-building to better integrate the factors operating at both individual and societal levels, and to better incorporate consideration of the influence of historical factors such as legacies of imperialism and colonial violence.

To investigate the impact of spatial positions of the transfer fork registration markers on the accuracy of generating a virtual dentofacial patient. An in vitro study was conducted using a mannequin head with a standard maxillary dentition model. Radiopaque gauge markers were fixed on the face and dentition of the mannequin head. CBCT was performed and the distance and angle between the dentition and facial markers were measured in the CBCT as reference values. Intraoral scanners were used to obtain 3D morphological data of the maxilla. Two types of transfer fork were designed and fabricated. The registration markers on transfer fork A were positioned in the midline area, while those on transfer fork B were located at the corners of the mouth on both sides. The transfer forks were digitised and connected to the maxillary dentition within the mannequin head, and facial scanning was performed using a facial scanner five times in each group. A virtual dentofacial patient was built through matching and integration of digital dentition, face and transfer fork data using 3D reverse engineering software (Geomagic Wrap 2021, 3D Systems, Rock Hill, SC, USA). Measurement values including feature lengths and feature angles between six facial gauge markers and three dentition gauge markers were obtained in the virtual patients. The mean trueness and precision of linear difference for virtual patients established using transfer fork A were -1.00 ± 0.11 mm and 0.27 ± 0.02 mm and the angle deviation was -1.88 ± 0.27 degrees, whereas for transfer fork B, the mean trueness and precision of linear difference were 2.66 ± 0.25 mm and 0.83 ± 0.06 mm, and the angle deviation was 3.74 ± 0.87 degrees. There is an overall significant difference in the trueness values of feature lengths (t = -13.963, P = 0.000) and angles (t = -5.985, P = 0.004) between transfer fork groups A and B, with group A showing better trueness and precision. Linear and angular errors will be introduced in the process of building up a virtual dentofacial patient using a transfer fork. The trueness and precision of the transfer fork with the matching markers at the centre of the lips are more precise than the transfer fork, with matching markers on both sides of the mouth.

School recess activities provide opportunities to enhance physical activity levels among adolescents. This study aims to explore factors influencing Chinese adolescents' participation in recess activities in urban and rural schools. A total of 49 participants (33 students, 16 teachers) were interviewed. Semi-structured interviews were used to collect primary data, including 2 focus group interviews and 36 one-on-one interviews. Data analysis was conducted using a grounded theory approach comprising three steps: open coding, axial coding, and selective coding. The framework derived from the data analysis aligned closely with the social ecological model (SEM), with identified factors spanning four levels of the SEM. Fifteen factors are distributed across the individual level (motivation to participation, body condition, academic pressure, and gender), interpersonal level (peer influence, teacher influence, and social interaction), physical environment level (equipment and facilities, accessibility of activity spaces, weather, and safety), and organizational and policy level (organized activities, physical activity design, recess duration, and school rules and regulations) of the SEM. Beyond these shared factors, we further identified 1 unique factor influencing urban schools (space size) and 2 unique factors influencing rural schools (motor skills and policy). The SEM provides a reference framework for understanding the factors influencing adolescents' participation in recess activities in urban and rural schools. Building on these identified factors, schools can design targeted recess activities and interventions to promote adolescents' participation. Notably, no relevant factors were found at the community level. Therefore, future research should examine potential factors at the community level.

A recent study by Thomas et al. (2022) showed that 8.5- to 10-month-olds use saliva sharing as an indicator of relationship closeness: infants expect that someone who previously shared saliva with a partner will also comfort that partner during times of distress. The current paper offers a mechanistic explanation for this finding. We propose that through everyday experiences, saliva sharing and comforting become integrated into an enriched representation that contains information about both events. Across five simulations, we show that when this proposal is implemented in a connectionist computational model, the model reproduces infants' looking behaviors in the study by Thomas et al. (2022) (Simulation 1), captures the finding that infants' responses were specific to comfort (Simulation 2), predicts bidirectional expectations about saliva sharing and comforting (Simulation 3), and shows that these expectations strengthen with experience and can shift in response to changes in environmental statistics (Simulations 4 and 5). Taken together, our findings suggest that domain-general associative learning can explain how infants come to understand the social meaning of saliva sharing. How do infants know who will help when someone is upset? Recent research shows that infants expect people who share saliva to comfort one another. The current study uses computer simulations to explain how infants develop this understanding. We propose that infants learn these social rules through everyday observations. By seeing people share saliva and provide support, infants learn to connect these two actions. Our simulations successfully explained infant behavior and showed that these expectations not only grow stronger with more experience but can also be reversed in extreme cases. This suggests that infants use general learning abilities to build an understanding of close relationships based on the patterns they observe in their daily lives.

Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), and platelets are significant biomarkers linked to pathological conditions like thrombosis, infection, and inflammation. Flow cytometry, paired with fluorescence staining, is commonly used to analyze these cell clusters, revealing cell morphology and protein profiles. While computational approaches based on machine learning have advanced the automatic analysis of single-cell flow cytometry images, there is a lack of effort to build tools to automatically analyze images containing CCCs. Unlike single cells, cell clusters exhibit irregular shapes and sizes. In addition, these cell clusters often consist of heterogeneous cell types, which require multi-channel staining to identify the specific cell types within the clusters. To address these challenges, we introduce a new computational framework for analyzing CCC images and identifying cell types within clusters. Our framework uses a two-step analysis strategy. First, it categorizes images into cell cluster and non-cluster groups by fine-tuning the You Only Look Once (YOLOv11) model, which outperforms traditional convolutional neural networks (CNNs), such as Vision Transformers (ViT). Then, it identifies cell types by overlaying cluster contours with regions from multi-channel fluorescence stains, thereby minimizing the impact of cell debris and staining artifacts. This approach achieved over 95% accuracy in both cluster classification and cell phenotype identification. In summary, our automated framework effectively analyzes CCC images from flow cytometry, leveraging both bright-field and fluorescence data. Initially tested on blood cells, it holds potential for broader applications, such as analyzing immune and tumor cell clusters, supporting cellular research across various diseases.

Adsorption behavior of emerging contaminants (ECs) plays a central role in their environmental fate and the efficiency of artificial removal systems. Machine learning (ML) has been extensively leveraged for adsorption prediction. However, most existing research focuses primarily on model construction and application, with limited attention to systematic challenges and corresponding solutions across the modeling workflow, thereby constraining model reliability and transferability. This review systematically summarizes key challenges in model construction, including data scarcity and bias, a low sample-to-feature ratio (SFR), inadequate feature representativeness, and inadequate model applicability and credibility. To address these challenges, this work consolidates a set of targeted improvement strategies, encompassing rigorous data quality assessment, automated feature extraction, cross-system modeling approaches, and the incorporation of external validation. Furthermore, we explore future development directions such as generative data augmentation, physics-informed machine learning (PIML), and automated literature data extraction via large language models. This work provides guidance for prospective ML model developers to build more robust and reliable models, laying the foundation for transformative advances in EC adsorption prediction research and applications.

Sociocultural barriers are powerful forces that may shape how young people experience, interpret, and respond to psychological distress in Zimbabwe. For many youth (aged 15-24 years), symptoms of common mental disorders (CMDs) are navigated within social environments where disclosure risks labelling, social exclusion, and moral judgment. This stigma is rarely experienced in isolation; it intersects with pressures to protect family reputation, distrust in formal and informal support systems, and gendered expectations governing emotional expression. While existing research has documented individual barriers to mental health care, limited evidence examines how these sociocultural forces converge to shape help-seeking pathways among Zimbabwean youth. This qualitative study explored how sociocultural factors influence decisions to seek or avoid care among young people with lived experience of CMDs. A descriptive qualitative research design was employed. We utilised in-depth interviews and focus group discussions with young people aged 15-24 years with lived experience of CMDs, their caregivers, peer counsellors, lay health workers, and church leaders in Harare and Bindura, Zimbabwe. Purposive sampling was employed to recruit participants until data saturation was reached. All interviews were audiotaped and transcribed verbatim, and all the data were analysed using inductive thematic analysis. The analysis revealed that help-seeking decisions were shaped by four interconnected sociocultural barriers; pervasive stigma; profound distrust in community and institutional spaces; family reputation pressures that prioritise concealment over disclosure; and restrictive gender norms that equate emotional expression with weakness, particularly among young men. Participants described how these factors intersect to create a dynamic where mental health concerns remain hidden rather than addressed. Our findings demonstrate that effective mental health interventions for Zimbabwean youth must address the multifaceted sociocultural landscape in which help-seeking decisions are made. Programmes need to simultaneously combat stigma, build institutional trust, engage families in destigmatisation efforts, as well as challenge restrictive gender norms. These strategies offer the most promising pathway to closing the mental health treatment gap for young people in Zimbabwe.

Health promotion in correctional settings faces challenges due to limited healthcare access and restricted environments. Nurses are primary healthcare providers in correctional institutions; however, evidence on nurse-led capacity-building programs for inmate health volunteers remains limited. Developing the capacity of Prison Public Health Volunteer Leaders (PPHVs) through a holistic healthcare approach can enhance their self-reliance. This study aimed to collaboratively develop, implement, and evaluate a holistic health care program to strengthen the capacity of PPHVs at the Central Correctional Institution for Young Offenders in Pathum Thani Province, Thailand. This study employed a Participatory Action Research (PAR) design. A total of 100 well-behaved inmates were purposively selected as PPHVs and actively engaged as co-participants throughout the PAR process. The intervention was collaboratively designed and implemented over five weeks, comprising ten participatory training sessions that addressed physical, mental, social, and environmental health dimensions. Quantitative data were collected using validated questionnaires assessing knowledge, attitudes, health practice skills, data management skills, and overall capacity at baseline, post-intervention, and at 1-month follow-up. Data were analyzed using repeated measures analysis of variance (ANOVA). The findings revealed statistically significant improvements (p <0.001) in participants' knowledge (F = 778.41, &#x3b7;p2 = 0.887), attitudes (F = 889.09, &#x3b7;p2 = 0.900), health practice skills (F = 1241.89, &#x3b7;p2 = 0.917), data management skills (F = 546.81, &#x3b7;p2 = 0.847), and overall capacity (F = 727.48, &#x3b7;p2 = 0.880). These outcomes indicate substantial enhancement in PPHVs' ability to perform health promotion and data management roles proficiently. The holistic health care program significantly improved PPHVs' capacity, suggesting promise for strengthening inmate health volunteer programs in correctional settings. These findings have significant implications for nursing practice in designing capacity-building programs, nursing education in preparing nurses for correctional care, and nursing policy in developing standards for correctional nursing in Thailand. Thai Clinical Trials Registry (TCTR20260115003).

Current decision-making for slope-reducing osteotomy (SRO) often relies on isolated posterior tibial slope (PTS) thresholds, potentially misidentifying patients with acquired soft-tissue decompensation or possibly overtreating those with an asymptomatic, inherently hyperlax baseline. Furthermore, rigid point-based scoring systems oversimplify the synergistic biomechanics of the anterior cruciate ligament-deficient knee. Building on the foundational 'Set-Point' theory established in Part 1, this paper introduces the assessment-led personalization (ALP) system. This unified clinical algorithm integrates the normalized percentage of absolute static anterior tibial translation (sATT%) and its side-to-side difference (&#x394;sATT%) with PTS laterality, generalized hyperlaxity, and injury chronicity. By mathematically calibrating raw translation data to isolate true soft-tissue decompensation from underlying osseous asymmetry, the ALP system provides a proactive, joint-preserving framework to identify high-risk phenotypes likely to fail isolated soft-tissue reconstruction and precisely refines the indications for SRO. LEVEL OF EVIDENCE: Level V.

To compare acute hemoglobin responses during bench press (BP) exercise among bodybuilders (BB), powerlifters (PL), Paralympic powerlifters (PP), and untrained controls (CON), with emphasis on relative load and sport background. Thirty-eight participants (BB, n&#x2009;=&#x2009;10; PL, n&#x2009;=&#x2009;10; PP, n&#x2009;=&#x2009;8; CON, n&#x2009;=&#x2009;10) performed ten BP repetitions at 20%, 40%, and 60% of one-repetition maximum (1RM). Multichannel functional near-infrared spectroscopy (fNIRS) was used to assess oxygenated hemoglobin (O&#x2082;Hb), deoxygenated hemoglobin (HHb), and total hemoglobin (tHb) responses over the C3-Cz-C4 region. Linear mixed models were used to test the effects of group, condition, and their interactions. The main effect of condition was significant for &#x394;O&#x2082;Hb in nine of ten channels and for &#x394;tHb in one channel (p_FDR_channel&#x2009;<&#x2009;0.05). No group effects or group&#x2009;&#xd7;&#x2009;condition interactions were observed for &#x394;O&#x2082;Hb, &#x394;HHb, or &#x394;tHb. Within-group post hoc analyses showed that &#x394;O&#x2082;Hb differences were observed mainly between 20 and 40% of 1RM (p_FDR_slice&#x2009;<&#x2009;0.05), with fewer additional differences involving 60% of 1RM. Acute hemoglobin responses during BP were expressed primarily as &#x394;O&#x2082;Hb changes and were associated with relative load under the present low-to-moderate load conditions. Because group effects and group&#x2009;&#xd7;&#x2009;condition interactions were not supported, these findings should be regarded as preliminary and descriptive rather than evidence of sport-specific adaptation or between-group differences in response magnitude. Observed O&#x2082;Hb changes represent regional hemodynamic responses, not direct measures of cortical activation or motor control processes.

Monitoring the growth dynamics in field-grown cabbage is critically important for ensuring stable vegetable production and advancing precision agricultural management. However, conventional two-dimensional (2D) image-based monitoring approaches are limited to planar projection information and lack representations of spatial structural characteristics, rendering them inadequate for supporting high-precision, full-cycle phenotypic monitoring of cabbage under open-field conditions. In this study, a high-precision three-dimensional (3D) point cloud dataset covering the period from the seedling stage to maturity was constructed using depth cameras in conjunction with multi-view spatial registration techniques. Building on this dataset, an adaptive point cloud segmentation network designed for the whole-cycle growth monitoring was proposed, incorporating a Head Refinement Module (HRM), a Leaf Instance Segmentation Module (LISM), and Cross Module Interaction (CMI) to address leaf adhesion and head boundary delineation. Experimental results demonstrated that the proposed method consistently outperformed state-of-the-art models in both semantic and instance segmentation tasks. For semantic segmentation, the mean Intersection over Union (mIoU) reached 0.767, with a point classification accuracy of 94.8%. The model comprises 54.25 million parameters and achieves an average response time of 0.76 s. For instance segmentation, the Average Precision (AP) improved by 2.3% for cabbage heads and 3.8% for leaves, while the Average Recall (AR) increased by 6.9%. Growth parameters, including plant height and canopy spread, extracted from the segmentation results showed strong agreement with ground-truth measurements, with correlation of coefficients (R2) exceeding 0.9 for plant height, canopy length, and canopy width. Leveraging these multidimensional phenotypic descriptors, the temporal dynamics of cabbage growth throughout the entire growth cycle were systematically characterized. Overall, this study enables dynamic monitoring of cabbage phenotypes across the full growth cycle, providing a novel technical pathway for extending 3D phenotyping from controlled environments to open-field applications and offering important support for precise crop monitoring and the development of digital twin agriculture.