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Problem: In Taiwan's hierarchical medical culture, postgraduate year (PGY) physicians face significant workplace challenges, exacerbated by Confucian values of hierarchical deference and collective harmony, which discourage open discussion of power imbalances. Approaches rooted in individualism, such as speaking-up initiatives and direct feedback pedagogies, encounter cultural barriers in this high-power-distance, collectivist context. While digital-native trainees increasingly use medical memes to express workplace frustrations, these community-generated expressions have not been systematically used for structured reflection in hierarchical medical education contexts. Intervention: In this pilot study, we designed a meme-based reflective learning curriculum integrating Kolb's experiential learning cycle, Palmer's "third things" approach, and Schön's mediating artifacts. Eight PGY physicians completed six monthly 90-minute sessions (January-June 2024), with follow-up interviews conducted six months post-intervention (December 2024). We curated memes from Taiwanese medical social media that depict workplace challenges, including hierarchical powerlessness, interprofessional tensions, emotional regulation, unclear workplace rules, time management, and patient-doctor communication. Sessions guided participants through Kolb's cycle: concrete experience (meme viewing), reflective observation (discussions), abstract conceptualization (consensus-building), and active experimentation (implementation). Context: The study was conducted at a medical center in Taiwan, where PGY physicians, competing for residency positions through an informal but widespread internal recruitment practice, faced intense pressure to maintain favorable impressions among seniors. This precarious status fostered reluctance to voice concerns as they navigated monthly rotations across departments with different cultures and unwritten rules. Impact: Participants demonstrated learning across all Kolb stages. Framed as an untested feasibility, the approach made previously unspeakable experiences discussable, creating resonance as participants recognized shared struggles. They developed practical strategies for emotional regulation and for navigating interprofessional relationships. However, encountering systemic barriers to implementation prompted an unexpected transformation: participants developed critical consciousness, shifting from seeking adaptation strategies to questioning the structures themselves. They articulated, "The problem isn't us. It's the whole unreasonable system," shifting the focus from coping to why this system exists. This evolution, which moves beyond an adaptation-focused curriculum toward Freire's dialogical education, emerged alongside a sense of powerlessness, as participants lacked the authority to enact structural change. Lessons learned: Drawing on Freire's concept of generative words, we theorize that community-generated memes functioned as generative artifacts: culturally embedded materials that fostered both workplace reflection and critical consciousness. This approach reframes Confucian collectivist orientations as empowering resources through what we term "safe subversion," in which humor's incongruity, ambiguity, and collective ownership keep critique within culturally tolerable limits. However, translating consciousness into structural change requires strategic alliances with educators who wield hierarchical authority in service of learning, bridging trainee awareness and institutional reform.

Endovascular thrombectomy transformed acute ischemic stroke care while exposing ethical tensions in emergency research. As landmark trials rapidly shifted standards, investigators faced complex questions regarding equipoise, early stopping, and respecting autonomy when patients lack capacity and time is critical. We conducted a focused literature analysis from 2003 to 2024 spanning practice-changing thrombectomy trials and contemporary ethics literature. We synthesized three domains: (1) equipoise dynamics during evidence accumulation; (2) balancing non-maleficence against the social value of continuing trials; and (3) consent models for incapacitated patients in time-sensitive settings. Initial uncertainty regarding endovascular efficacy justified early randomized controls. However, post-2015 data precipitated a rapid loss of equipoise, necessitating the early termination of trials to uphold the duty of care for control arm participants. While early stopping rules successfully minimized harm, they raised tensions regarding the precision of treatment effect estimates. Furthermore, the requirement for standard informed or surrogate consent was found to introduce selection bias against severe stroke patients lacking capacity. The literature supports shifting toward deferred or presumed consent models in these emergencies, arguing that rigid adherence to autonomy can paradoxically violate the principles of justice and beneficence by systematically excluding the most vulnerable patient populations from life-altering interventions. Ethical conduct of emergency stroke trials requires continuous reassessment of equipoise, pre-specified stopping rules that prioritize participant welfare, and consent pathways tailored to incapacity and time sensitivity. We explore principles integrating beneficence, non-maleficence, autonomy, and justice to maximize lives saved and prevent disability while preserving rights. These principles generalize to future trials as indications, technologies, and timelines evolve.

In examination-centered education systems, career guidance frequently reproduces inequality rather than reducing it. South Africa illustrates this pattern. The Curriculum and Assessment Policy Statement (CAPS) requires career guidance through the required course Life Orientation (LO). However, LO has a structurally marginal position within CAPS because it is not evaluated externally and is not included in the point calculations used by the majority of South African universities for admission. The result is a compliance gap between policy intent and the institutional conditions required to realize that policy. This conceptual review develops a theoretical framework that explains how curriculum governance produces and reproduces career guidance inequality. Its central argument is that curriculum classification and framing rules act as structural-environmental conversion conditions which mediate whether learners can convert formal access to career guidance into substantive vocational capability. The framework integrates the sociology of knowledge with the Capability Approach. It draws on classification, framing, and recontextualization to explain curriculum governance, and on conversion factor theory to explain how institutional conditions shape capability development. Existing research on South African career guidance is used illustratively to ground four conceptual propositions. The manuscript's principal theoretical contribution is the conceptualization of curriculum classification and framing rules as a form of structural-environmental conversion condition, an institutional configuration that mediates the transformation of career guidance resources into substantive vocational capability. The review is conceptual rather than systematic in design. Career guidance inequality is not primarily a deficit of learner aspiration. It is a consequence of institutionally patterned conversion conditions. The framework carries implication for any examination-centered system in which subjects are differentially governed and resourced.

The dentate gyrus is a key relay station that controls information transfer from the entorhinal cortex to the hippocampus proper. This process relies heavily on dendritic integration by dentate granule cells (GCs) of excitatory synaptic inputs from the medial and lateral entorhinal cortex via medial and lateral perforant paths (MPP and LPP, respectively). Inputs from the entorhinal cortex onto GCs exhibit activity-dependent long-term plasticity of N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic transmission. However, the properties, underlying mechanisms, and input-specificity of this plasticity remain poorly understood. Here, we examined NMDAR plasticity rules at MPP-GC and LPP-GC synapses using physiologically relevant stimulation patterns in acute hippocampal slices from rats and mice. Unlike MPP-GC synapses, LPP-GC synapses did not express homosynaptic NMDAR-LTP. Additionally, inducing NMDAR-LTP at MPP-GC synapses potentiated NMDAR transmission at distal LPP-GC synapses. The same stimulation protocol induced homosynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-LTP at MPP-GC synapses but heterosynaptic AMPAR-LTD at distal LPP synapses, indicating that NMDAR and AMPAR plasticity are controlled by different plasticity rules. Notably, heterosynaptic but not homosynaptic NMDAR-LTP required Ca2+ release from intracellular, ryanodine receptor-dependent Ca2+ stores. Lastly, genetic deletion of the GluN2D subunit from GCs or selective antagonism of GluN2D-containing NMDARs abolished heterosynaptic LTP. Heterosynaptic NMDAR-mediated LTP may have important consequences for the dendritic integration of functionally distinct excitatory inputs by dentate granule cells.

Severe burns impair the body's natural healing capacity, often resulting in delayed tissue repair. Platelets facilitate hemostasis and initiate wound healing through growth factor release. This study investigates the therapeutic potential of collagen nanofibers enriched with Plasma Rich Growth Factors (PRGF) to enhance cell proliferation, migration, and wound healing in burn injuries. PRGF powder was prepared from whole blood using a two-step centrifugation protocol followed by freeze-thaw activation and incorporated into collagen/polyethylene oxide (COL/PEO) electrospun nanofibers. The physicochemical properties and growth factor release profile of the nanofibers were characterized. In vitro assays evaluated the effects of PRGF-loaded nanofibers on fibroblast viability and migration. For in vivo analysis, a standardized full-thickness burn wound model was induced in male Wistar rats following Orio's rules. Wound healing was assessed over a 21-day period through macroscopic wound closure measurements and histological analyses, including H&E staining, Masson's trichrome staining, and VEGF immunohistochemistry. PRGF-loaded collagen nanofibers showed an initial burst release of growth factors followed by sustained release. In vitro, PRGF incorporation significantly enhanced fibroblast viability and migration. In vivo, the PRGF + COL/PEO group demonstrated markedly accelerated wound healing, with improved re-epithelialization, reduced inflammation, greater fibroblast infiltration, and more organized collagen deposition. VEGF expression peaked at day 14, indicating increased angiogenesis, and declined by day 21 as vascular remodeling progressed. Collagen nanofibers enriched with PRGF provide a promising wound dressing that promotes cell proliferation and migration, accelerating burn wound repair. The absence of leukocytes in PRGF compared to platelet-rich plasma (PRP) further supports its therapeutic advantage in tissue regeneration.

Infection-induced bone defects are a challenging disease in orthopedic clinical practice. Traditional treatments face core problems such as limited bone sources, high risk of antibiotic systemic application-induced resistance, and difficulties in synchronizing infection control and bone regeneration. 3D printing technology, with its advantages of personalized customization, precise structural regulation, and compatibility and adaptability of multiple materials, has become the core preparation method for repair scaffolds for infection-induced bone defects. Constructing an integrated scaffold with three functions - antibacterial, osteogenic, and vascularization - that is temporally coupled and spatially stratified, and oriented towards clinical translation is a key direction to break through the treatment bottleneck of this disease. This review differs from existing reviews that only focus solely on antibacterial materials, 3D printing scaffold preparation, or bone regeneration mechanisms. It is the first to systematically construct a three-function collaborative framework of "infection control - angiogenesis - bone regeneration" with temporal coupling and spatial stratification. It deeply analyzes the adaptability of different material systems in the infection microenvironment, the logic of selecting anti-infection strategies, and the design rules of biomimetic structures. It comprehensively summarizes the key bottlenecks in clinical translation, real clinical case evidence, and industrialization paths, and clarifies the time-controlled regulatory mechanism and clinical translation targeting path of the three-function collaboration. 3D printed anti-infection bone scaffolds can achieve synchronous repair of infection clearance, bone regeneration, and angiogenesis. The three-function temporal and spatial collaborative design and integrated research for clinical translation are the core development directions in this field, providing theoretical support and practical guidance for the precise treatment of infection-induced bone defects.

Soft-tissue sarcomas (STSs) are a complex and remarkable heterogeneous group of uncommon malignancies originating from fat, muscle, and other connective tissues. They constitute approximately 1% of all cancers with 50 to 70 distinct histologic subtypes or tumor entities. This type of tumor, also known as "the loneliest cancer" because of its rarity, can manifest at any age, but they are most commonly diagnosed in individuals older than 40 years. They can rise from any anatomic location (somatic, visceral, or bone), but the extremity is the most common primary site. STS presents a notable clinical challenge due to its gradual onset and variable symptoms. Consequently, soft-tissue masses should be thoroughly evaluated to rule out malignancy. Some STSs can be aggressive and tend to have high recurrence and metastasis rates (40-50%), particularly in the lungs (80% of the cases) and less often in the liver, brain, bones, and peritoneum, where their occurrence might indicate a poor prognosis. The fact that they are rare and their histologic morphology varies and sometimes can overlap with different genetic, molecular, and clinical profiles contributes to their delayed and complex diagnoses. A high index of suspicion, coupled with appropriate clinical and radiologic assessment and biopsy, can help identify STS. A systematic, multidisciplinary team (e.g., orthopaedic surgeons, oncologists, radiologists, and pathologists) approach is essential for accurately diagnosing and treating soft-tissue sarcomas. Correlating clinical and radiologic information and involving a multidisciplinary team aid in accurate diagnosis. Biopsy, a crucial step, requires rigorous rules and appropriate technique selection. Histologic diagnosis can be challenging because of limited material and divergent interpretations. Advanced tools such as immunophenotypic panels and genetics can enhance accuracy. The fifth edition of the WHO manual can classify soft tissue, while the AJCC-TNM system can stage tumors. Surgical resection, often supplemented with radiation and chemotherapy, is the primary treatment for STS. However, some subtypes (e.g., liposarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma) have high local recurrence rates or metastasis, leading to inconsistent treatment outcomes. Innovative immune and radiation therapy treatment regimens and targeted therapy can offer potential effective alternatives for these challenging cases.

Right-hook crashes in right-hand traffic where cyclists going straight are struck by right-turning vehicles pose a major safety concern. This study aims to establish to which extent such conflicts may stem from non-driving-related tasks (NDRT), low saliency of cyclists (covertness), or drivers' insufficient knowledge of applicable rules. Forty-four drivers participated in a fixed-base driving simulator study using an extended reality (XR) setup with integrated eye tracking. Participants were stratified by urban cycling experience (cyclist-drivers vs. drivers) and self-reported driving style (cautious vs. assertive). Each drove an urban route including 12 right-turn-on-yield scenarios, with and without NDRT. Observed visual sampling was combined with a questionnaire-based rule knowledge assessment to examine whether scanning failures were due to workload or lack of rule knowledge. NDRT engagement primarily reduced default glances while glances to relevant areas (Left, Right, Over Shoulder) were preserved. Over-the-shoulder checks were rare overall. In 85 % of right-turns, no such glance occurred before turning, regardless of NDRT status. Rule knowledge mirrored these patterns, with drivers being more likely to correctly indicate the requirement to yield to salient crossing traffic streams of cars (96 % correct) or cyclists and pedestrians (81 % correct) than non-salient crossing bicycle or pedestrian traffic (46 % correct). Drivers with cycling experience scored slightly better overall but still missed nearly half of the non-salient yielding requirements. The findings indicate that gaps in rule knowledge contribute to failures to check for cyclists. Countermeasures should prioritise systemic interventions, complemented by education, rather than solely relying on behaviour-focused measures.

Shared beliefs in social interactions evolve through opinion exchanges governed by hybrid time scales and heterogeneous update rules. In this letter, we rigorously analyze hybrid opinion dynamics (HOD) of an interacting continuous-discrete dyad. By characterizing the HOD via a stroboscopic map, we analytically establish that high reactivity triggers a local flip bifurcation that destabilizes consensus. Following this loss of stability, the opinion trajectories enter a saturated plateau-switching regime and converge to a stable indecisive limit cycle representing a persistent cyclic deadlock. Leveraging Floquet theory and a Lyapunov-based cycle-to-cycle contraction, we prove the asymptotic stability of these oscillations. Finally, we propose a social-attention-based control law that guarantees a transition from cyclic deadlock to consensus.

Bioacoustic data from passive acoustic monitoring (PAM) generates large datasets where obtaining detailed auditing and labelling is often impractical, resulting in weak annotations (e.g., presence/absence of species over several minutes of recording). In order to effectively capture the complex temporal patterns and key features of long audio segments, we propose a framework comprising dataset standardisation, feature extraction, and classification via temporal convolutional networks (TCN). This approach eliminates the necessity for setting heuristic decision rules or creating time-consuming strong labels. To demonstrate the effectiveness of our approach, we use sperm whale (Physeter macrocephalus) click trains in 4-min recordings as a case study, from a dataset comprising diverse sources and deployment conditions to maximise generalisability. Our TCN classifiers achieve recall rates exceeding 0.83 at a 0.13 false positive rate, comparable to agreement rates between expert annotators. We compare two methods of feature extraction, variational autoencoders (VAEs) and traditional handpicking of features, and found them to yield similar performance results, with the VAE-based classifiers seeing a more stable performance across datasets and recording conditions. These results offer a way forward in leveraging numerous existing annotated bioacoustic datasets to train automatic classification models, effectively overcoming previous limitations associated with weak labels.

Wetland degradation and areal loss driven by global change and intensified human activities pose increasing challenges to wetland conservation and restoration. Reliable decision-making requires accurate identification of wetland extent and type, which is currently dominated by remote sensing-based mapping. However, gradual wetland boundaries, high intra-class heterogeneity, and spectral similarity among land-cover types often lead to classification uncertainty. Concealed wetlands are particularly prone to omission because of canopy obstruction, temporary absence of open water, and weak spectral separability. More importantly, remote sensing products alone have limited capacity to explain the hydrological mechanisms governing wetland expansion, contraction, and persistence under varying flow regimes. Hydrological connectivity provides a process-based perspective for linking wetland occurrence and function to runoff generation, lateral flow redistribution, and groundwater-surface water interactions within watersheds. To address these limitations, this study developed a SWAT+-based hydrological connectivity wetland classification system, termed SWAT+ HWC. Driven by physically based simulations at the hydrological response unit (HRU) scale, SWAT+ HWC provides a transferable framework for candidate wetland screening and functional wetland classification. Daily HRU-scale fluxes and state variables were used to derive ten process indicators characterizing dominant hydrological connectivity mechanisms, and candidate wetlands were further classified into three functional units: riparian wetlands, shallow depressional wetlands, and deeply connected wetlands. Classification thresholds were adaptively calibrated in quantile space using a particle swarm optimization-classification and regression tree algorithm combined with a K-out-of-N voting rule, thereby constraining the candidate wetland proportion while improving the spatial transferability of classification rules across watersheds with contrasting hydrogeomorphic settings. Model performance was evaluated through process-consistency analysis, quantitative comparison with the WetlandConnectivity v1.0 dataset, and spatiotemporal validation in the Altamaha River Basin. The identified wetland types showed stable correspondence with their expected dominant hydrological indicators. Quantitative evaluation demonstrated strong discriminatory performance across representative geomorphic units, with most ROC-AUC values ranging from 0.89 to 0.95, and seasonal wetland-area dynamics were highly synchronized with the reference dataset, with correlation coefficients exceeding 0.84. By linking wetland identification to testable hydrological process chains, SWAT+ HWC provides a physically traceable basis for wetland mapping, functional interpretation, and cross-period comparison. The resulting hydrological connectivity-based classification enables wetland mapping to move beyond identifying where wetlands are located toward explaining why wetlands occur and persist in specific landscape positions, thereby improving the interpretability and targeting of wetland conservation, ecological restoration, and watershed water resources management.

CD spectroscopy is the essential tool to quickly ascertain in the far UV region the global conformational changes, the secondary structure content and protein folding and in the near UV region the local tertiary structure changes probed by the local environment of the aromatic side chains, prosthetic groups (hemes, flavones, carotenoids), the dihedral angle of disulphide bonds and the ligand chromophore moieties, the latter occurring as a result of protein-ligand binding interaction. Qualitative and quantitative investigations into ligand binding interactions in both the far-UV and near-UV regions using CD spectroscopy provide unique and direct information whether induced conformational changes upon ligand binding occur and of what nature that are unattainable with other techniques such as fluorescence, ITC, SPR, and AUC. This chapter provides an overview of how to perform circular dichroism (CD) experiments, detailing methods, hints, and tips for successful CD measurements. Descriptions of different experimental designs are discussed using CD to investigate ligand-binding interactions. This includes standard qualitative CD measurements conducted in both single-measurement mode and high-throughput 96-well plate mode, CD titrations, and UV protein denaturation assays with and without ligand. The highly collimated microbeam available at B23 beamline for synchrotron radiation circular dichroism (SRCD) at diamond light source (DLS) offers many advantages to benchtop instruments. The synchrotron light source is ten times brighter than a standard xenon arc light source of benchtop instruments. The small diameter of the synchrotron beam can be up to 160 times smaller than that of benchtop light beams has enabled the use of small aperture cuvette cells and flat capillary tubes reducing substantially the amount of volume sample to be investigated. Methods, hints and tips, and golden rules to measure good quality, artifact-free SRCD and CD data will be described in this chapter in particular for the study protein-ligand interactions and protein photostability.

Microbially induced calcium carbonate precipitation (MICP) can transform granular media into cohesive, load-bearing materials, yet pore-scale design rules linking geometry, transport, and mineral growth remain difficult to pin down. Here we present a resin-molded microfluidic pore-network platform that mimics coarse-aggregate architectures relevant to living building materials and allows controlled variation of pore geometry. Devices loaded with Sporosarcina pasteurii were imaged using paired brightfield and transmitted-light polarization microscopy to resolve structure and quantify birefringent CaCO3. Automated image segmentation constrained analysis to the pore space, enabling high-throughput extraction of precipitation coverage, particle density, and feature size across hundreds of fields. Across the tested range, precipitation outcomes depended on channel height and porosity, whereas pillar diameter showed no measurable effect on coverage when porosity and height were fixed. Lower porosity tended to increase particle density but limit feature growth, while higher porosity and taller channels favored larger, coalescing deposits and more spatially continuous films. These patterns are consistent with transport shaping which regime occurs: channel height and porosity together appear to set diffusive replenishment and byproduct dilution, shifting mineralization between a nucleation-dominated regime of many small deposits and a coalescence-dominated regime of fewer, larger features.

Automated blood cell separators are commonly used for autologous platelet-rich plasma (PRP) preparation. Although these devices ensure stable platelet concentrations, low contamination, and high reproducibility, unified protocols remain lacking. This study explored a collection protocol that uses real-time visual feedback and dynamic parameter adjustment. In this single-center retrospective study, we analyzed 35 autologous PRP collections. Visual criteria (pale lemon-yellow appearance, uniform turbidity, absence of macroscopically visible particles) and adjustment rules were developed. Platelet concentration, enrichment factor, and residual red blood cell (RBC) and white blood cell levels were assessed. Median platelet concentration was 1500 × 109/L (IQR, 1031-1618 × 109/L), and the mean (SD) enrichment factor was 6.33 (2.76); 71.43% (25/35) of products fell within a range of 1000 to 1800 × 109/L, consistent with reported 3-fold to 8-fold enrichment. Red blood cell counts ranged from 0 to 0.20 × 1012/L. No macroscopic RBCs were detected, but 37.1% (13/35) of RBCs exceeded a threshold of 0.05 × 1012/L. White blood cell counts ranged from 0 to 1.69 × 109/L, below the leukocyte-poor threshold proposed by Kikuchi et al. This study presented a protocol capable of producing PRP within the therapeutic range and achieving effective leukocyte control. Our findings provide a practical strategy for translating subjective experience into objective, trainable procedures. Given the limitations of small sample size and subjective visual criteria, further prospective machine vision validation is warranted.

Germline GATA2 deficiency is a pleiotropic condition 1-8 characterized by numerous phenotypes, including monocytopenia, immunodeficiency, microbial susceptibilities, and high rates of myeloid malignancies 1,8. Accurate curation of germline GATA2 variants is critical for patient care and requires well-defined phenotypes associated with GATA2 deficiency. The many phenotypes attributed to the condition render a simple description of GATA2 deficiency difficult, complicating the development of GATA2 variant curation rules. Therefore, the Myeloid Malignancy Variant Curation Expert Panel (MM-VCEP) sought to define GATA2 deficiency based on a statistical comparison of phenotype data. To do so, the MM-VCEP systematically analyzed phenotype data and applied statistical comparisons to define the phenotypic features of GATA2 deficiency to inform germline variant curation. The MM-VCEP assembled an international cohort of 339 people with clinically diagnosed GATA2 deficiency from 16 centers in seven countries. The 73 phenotypes of these individuals were compared statistically to those of control participants from the UK Biobank (UKBB). We compared single phenotypes as well as combinations of two, three, and four phenotypes in people with clinically diagnosed GATA2 deficiency to UKBB controls. We defined GATA2 deficiency as any of the 2,903 combinations of two or three phenotypes with log10Odds Ratio ≥3 (OR ≥ 1000). This definition of GATA2 deficiency will inform gene-specific phenotypic criteria used in GATA2 variant curation guidelines that will facilitate standardized variant curation by clinical laboratories worldwide.

Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth. To make reliable inferences, such models must be able to reflect the properties of real tumors. Recent work has shown that lung tumors undergo frequent and late subclonal expansions, which are associated with poor prognosis. This paper tests three candidate simulations of three-dimensional tumor growth, which make different assumptions about the nature of competition between cells, for their ability to replicate these late expansions. The study identifies a computationally-efficient model which can produce multi-region sequencing data realistic to lung tumors. This model assumes two distinct stages of growth, with the second stage involving local competition for space and resources within and between small tissue areas in a fixed-size tumor. When inferring the model-specific fitness effect of driver mutations in a large cohort of lung cancers, the study finds that inference pipelines based on a two-stage model imply much larger selection effects than those based on single-stage models, driven by model-specific assumptions about the practical consequences of selection strength. This work emphasizes the importance of model assumptions to the results of tumor-specific, simulation-based inferences.

Postoperative complications afflict approximately 40% of patients undergoing colorectal cancer (CRC) surgery and adversely affect long-term oncological outcomes. Reliable perioperative risk stratification tools that are both clinically interpretable and actionable remain limited. This retrospective cohort study enrolled 1,013 consecutive patients undergoing elective radical resection for histopathologically confirmed CRC at a single tertiary center. A nine-system composite complication endpoint was defined. Missing data were handled via multiple imputation by chained equations (MICE; m = 5). Candidate predictors were screened by univariable logistic regression and LASSO regularization; final predictors were entered into multivariable logistic regression with Rubin's rules pooling. Model performance was assessed by AUC, bootstrap internal validation (1,000 iterations), Hosmer-Lemeshow calibration, and decision curve analysis (DCA). A nomogram was constructed for individualized risk estimation. Of 1,013 patients, 372 (36.7%) experienced ≥1 postoperative complication. LASSO selected eight independent predictors: NRS-2002 nutritional risk score (aOR 1.502, 95% CI 1.312-1.720), laparoscopic approach (aOR 0.457, 95% CI 0.297-0.702), intraoperative blood loss (aOR 1.002/mL), right colon tumor location (aOR 1.502), NLR (aOR 1.080/unit), operative time (aOR 1.002/min), hemoglobin, and total bilirubin. The model achieved an apparent AUC of 0.689 (bootstrap-corrected 0.680), satisfactory calibration (Hosmer-Lemeshow p = 0.709), and net clinical benefit across threshold probabilities of 10-90% on DCA. Sensitivity analyses confirmed robustness across four pre-specified scenarios (AUC range 0.666-0.715). This LASSO-derived nomogram provides transparent, bedside-applicable risk stratification for postoperative composite complications in CRC surgery, identifying nutritional status as the dominant modifiable predictor and supporting targeted perioperative optimization.