Search Results (278)

Platelet-rich plasma (PRP) has emerged as one of the most extensively investigated orthobiologic therapies for tendon disorders because of its potential to modulate inflammation, enhance extracellular matrix remodeling, and promote tissue regeneration through the delivery of concentrated platelets and bioactive molecules. However, despite compelling biological rationale and encouraging preclinical evidence, clinical outcomes remain inconsistent across different tendon pathologies. This narrative review critically examines the principal biological and methodological factors underlying this variability, including differences in cellular composition, growth factor and cytokine profiles, activation strategies, and current PRP classification systems. We further synthesize the available clinical evidence across major tendon disorders, highlighting the influence of disease-specific biology, product heterogeneity, and procedural variability on treatment response. In addition, the emerging role of quantitative imaging biomarkers in objectively evaluating tendon regeneration is discussed as a complementary tool for biological outcome assessment. Based on the evidence reviewed, we propose the quantifiable platelet-rich plasma (Q-PRP) framework, a practical reporting model that integrates cellular, molecular, procedural, and clinical variables into a standardized approach for biologically meaningful PRP characterization. Rather than replacing existing classification systems, the proposed framework aims to improve reproducibility, facilitate cross-study comparison, and support the transition toward precision regenerative medicine. Standardized biological characterization, combined with objective outcome assessment, may represent a critical step toward optimizing PRP research and clinical application in tendon healing. Full article

Background: Parkinson’s disease (PD) exhibits remarkable clinical heterogeneity, with substantial variability in motor progression, cognitive decline, and the development of non-motor manifestations. Although the propagation of pathological alpha-synuclein is considered a central mechanism of PD pathogenesis, it does not fully explain why specific neuronal populations demonstrate differential susceptibility to degeneration. Emerging evidence suggests that selective neuronal vulnerability is determined by the interaction of multiple biological domains, including calcium homeostasis, mitochondrial bioenergetic capacity, lysosomal function, axonal architecture, synaptic resilience, and neuroinflammatory responses. Methods: A structured critical narrative review was performed using PubMed/MEDLINE, Scopus, and Web of Science databases from inception to March 2025. Only full-text articles published in English and peer-reviewed journals were included. Evidence from human post-mortem studies, genetic analyses, biomarker investigations, experimental models, induced pluripotent stem cell studies, and longitudinal clinical cohorts were systematically synthesised to identify the principal mechanisms underlying selective neuronal vulnerability and their potential translational application. To capture evidence published after this electronic cut-off, a supplementary manual review of reference lists of key systematic reviews and landmark publications was conducted up to the date of manuscript submission; references with 2025 or 2026 publication dates entered through this supplementary process. The supplementary manual review was conducted as a targeted scan of reference lists of key systematic reviews and high-impact publications identified during the primary search and did not constitute an independent updated systematic search. Results: Five interconnected biological domains emerged as key determinants of neuronal susceptibility in PD: calcium-mediated metabolic stress associated with autonomous pacemaker activity, mitochondrial dysfunction and energetic failure, impaired lysosomal degradation and proteostasis (particularly involving the GBA1–glucocerebrosidase pathway), vulnerability related to extensive axonal and synaptic architecture, and neuroinflammatory mechanisms involving microglial and astrocytic activation. Among these domains, the lysosomal pathway currently provides the strongest translational link between molecular mechanisms and measurable clinical outcomes. Based on this integrated framework, we propose the Parkinson’s Vulnerability Index (PVI), a hypothesis-generating multidimensional model combining genetic, enzymatic, alpha-synuclein seeding, cognitive, olfactory, and neuroimaging biomarkers to facilitate biological stratification and improve the design of mechanism-targeted clinical trials. Conclusions: Selective neuronal vulnerability provides a complementary framework to alpha-synuclein propagation models for understanding the heterogeneity of PD. The proposed PVI is not intended as a diagnostic or prognostic clinical instrument but as a research tool requiring prospective validation. Future precision medicine approaches in PD may benefit from integrating vulnerability-related biomarkers with existing biological staging systems to identify patients most likely to benefit from targeted disease-modifying therapies. Full article

Background: Cholangiocarcinoma (CCA) is a highly heterogeneous malignancy with limited therapeutic options and poor prognosis. The increasing complexity of molecular stratification and treatment selection has stimulated interest in computational and biological modeling approaches for precision oncology. Objective. This narrative review aims to provide a comprehensive overview of digital twins (DTs), DT-enabling computational models, and biological twins (BTs) in CCA, discussing their applications, limitations, and potential integration within hybrid precision medicine frameworks. Methods: A narrative literature review was conducted. To inform the twin-focused sections, a structured PubMed search was performed using predefined keywords related to CCA and twin-related technologies, including organoids, xenografts, organ-on-chip systems. Particular attention was devoted to recent studies addressing computational modeling, patient-derived experimental systems, and translational applications. Results: DT development in CCA is supported by an ecosystem of DT-enabling technologies, including radiomics, artificial intelligence, multi-omics integration, and simulation-based models. However, fully realized medical DTs remain unavailable. BTs, including patient-derived organoids, xenografts, and microfluidic platforms, enable functional validation of therapeutic hypotheses but face challenges related to scalability, standardization, and clinical feasibility. Emerging hybrid DT-BT frameworks seek to combine computational prediction with biological validation through iterative feedback loops, potentially improving patient stratification and treatment personalization. Conclusions: DTs and BTs represent complementary components of an evolving precision oncology ecosystem in CCA. Although technical, biological, regulatory, and implementation challenges remain, the convergence of computational models, longitudinal molecular monitoring, and patient-derived systems may facilitate clinically actionable hybrid twin frameworks. Successful translation will require both technological innovation and healthcare-system improvements to precision medicine access. Full article

Despite substantial progress in biomarker discovery and multi-omics profiling, several features of Alzheimer’s disease (AD), including prolonged compensated states, heterogeneous clinical trajectories, and marked stage-dependent therapeutic responses, remain difficult to integrate into a single mechanistic framework. In this review, we propose an integrative and testable conceptual framework that reframes AD as a single, progressive multi-layer network disorder whose dynamics arise from hierarchical constraint propagation and progressive loss of cross-scale coordination. Integrating evidence from human genetics, epigenomics, transcriptomics, proteomics, metabolomics, spatial biology, connectomics, and longitudinal biomarker studies, we examine how molecular, cellular, and circuit-level processes interact over time to shape disease progression. Within this framework, different omics measurements are interpreted as complementary representations of disease-related changes, rather than as independent molecular signatures. Disease progression reflects the gradual convergence of immune, metabolic, proteostatic, cytoskeletal, and synaptic stress, with overt cognitive impairment emerging when compensatory capacity is exceeded, producing threshold-like network destabilization. By explicitly linking biological scale, temporal hierarchy, and network structure, this synthesis extends prior network-medicine, connectomic, and multi-omics approaches into a testable framework for state-aware stratification, integrative analysis, and stage-appropriate therapeutic investigation in AD. Full article

The genus Agastache comprises aromatic and medicinal plants of increasing interest for the diversification of high-value crops. Among them, Agastache foeniculum (Pursh) Kuntze and Agastache mexicana Lint. et Epling represent two contrasting yet complementary models of multipurpose medicinal and aromatic species. This review critically compares both species with respect to taxonomy, origin, domestication, agronomic performance, phytochemical diversity, biological activities, quality standardization, safety, regulatory status, and industrial applications. Current evidence indicates that A. foeniculum is well adapted to temperate cultivation systems and represents a valuable source of essential oils and polyphenol-rich biomass, whereas A. mexicana offers considerable potential for the development of standardized nutraceutical, cosmetic, and phytopharmaceutical products. Nevertheless, the broader commercialization of both species remains constrained by pronounced chemotype variability, limited multi-site agronomic validation, insufficient clinical evidence, safety concerns associated with certain volatile constituents, and an evolving regulatory framework. The available evidence underscores the need to move beyond descriptive studies toward integrated crop development strategies that combine metabolomics-based chemotype classification, genomic and transcriptomic analyses, breeding for stable and safe phytochemical profiles, polyploidy-assisted improvement, climate-smart cultivation practices, and standardized post-harvest processing. Collectively, these approaches will facilitate the sustainable exploitation of both species and support their transition from promising medicinal and aromatic plants to commercially viable, high-value multipurpose crops for sustainable agriculture. Full article

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) remain the cornerstone of pharmacological treatment for osteoarthritis (OA) and are recommended by international guidelines for the management of symptomatic pain. Despite their well-established efficacy, substantial interindividual variability exists in treatment response, with some patients experiencing meaningful pain relief while others derive little clinical benefit despite appropriate drug selection and dosing. This variability reflects, at least in part, the biological heterogeneity of OA pain. Objective: To review the mechanisms underlying variability in NSAID responsiveness in OA and to propose a practical framework for personalized NSAID prescribing based on pain phenotype, individual safety profile, and treatment timing. Methods: A narrative review of the contemporary scientific literature was conducted using major biomedical databases to summarize the current evidence on phenotype-guided NSAID therapy in OA. Particular attention was given to the emerging concepts of nociceptive, nociplastic, and neuropathic-like pain phenotypes and their implications for personalized anti-inflammatory therapy. Results: Current evidence indicates that OA pain is a heterogeneous and dynamic condition in which inflammatory nociceptive, nociplastic, and neuropathic-like mechanisms coexist to varying degrees. NSAIDs primarily target inflammatory nociceptive pain by inhibiting cyclooxygenase (COX)-mediated prostaglandin synthesis and reducing peripheral sensitization. Consequently, patients with predominantly inflammatory nociceptive pain are the most likely to benefit from NSAID therapy, whereas those with predominant nociplastic or neuropathic-like pain mechanisms may require alternative or multimodal treatment strategies. Beyond pain phenotype, optimal NSAID selection should integrate cardiovascular, gastrointestinal, and renal risk assessment, recognizing the important pharmacological and safety differences among individual agents. Treatment timing is also clinically relevant, as anti-inflammatory therapy appears most effective when initiated during periods of active inflammatory nociceptive pain. Based on the available evidence, we propose a conceptual clinical decision framework integrating patient selection, NSAID choice, and treatment timing. Conclusions: Personalized NSAID prescribing should move beyond a diagnosis-based approach toward a mechanism-based strategy that integrates pain phenotyping, individualized safety assessment, and appropriate treatment timing. The proposed framework is built upon three complementary principles, identifying the right patient, selecting the right treatment, and initiating therapy at the right time. It provides a practical foundation for implementing precision medicine in the pharmacological management of OA. Full article

Background/Objectives: Early identification of breast cancer patients unlikely to benefit from neoadjuvant chemotherapy (NAC) remains a pressing clinical problem because ineffective therapy delays definitive surgery and exposes patients to unnecessary toxicity. Quantitative ultrasound (QUS) and shear wave elastography (SWE) probe complementary tissue properties—scatterer microstructure and mechanical stiffness—that may change before macroscopic tumor shrinkage. This study aimed to evaluate whether multi-parametric ultrasound (mpUS) radiomic kinetics, analyzed with a machine learning ensemble and interpreted with SHAP, could predict pathologic response to NAC. Methods: A prospective observational cohort enrolled 135 women with biopsy-proven stage II–III breast cancer treated with NAC within the multidisciplinary breast pathway shared between Vasile Goldis Western University of Arad and Victor Babes University of Medicine and Pharmacy Timisoara (Pius Brinzeu County Emergency Hospital). All patients underwent standardized QUS and SWE acquisitions at baseline, week 1, and week 3. Response was defined pathologically at surgery as residual cancer burden (RCB) class 0/I versus II/III. Group comparisons used Welch’s t-test, Mann–Whitney U, chi-square, and Fisher’s exact tests; correlations used Spearman’s rho. A stacked machine learning ensemble (four base learners—XGBoost, random forest, support vector machine, and L2-penalized logistic regression—combined by a separate second-stage logistic meta-learner) was trained with nested 10-fold cross-validation, bootstrap stability assessment, SHAP-based interpretability, and decision curve analysis. Results: Sixty patients (44.4%) were responders and 75 (55.6%) were non-responders. Responders showed greater week 3 increases in mid-band fit (3.4 ± 0.9 vs. 1.2 ± 0.8 dB, p < 0.001), entropy (0.7 ± 0.2 vs. 0.2 ± 0.2, p < 0.001), and more pronounced SWE mean stiffness reduction (−44.1 ± 9.7 vs. −12.1 ± 8.6 kPa, p < 0.001). The stacked ensemble integrating clinical, QUS, and SWE kinetic features reached an AUC of 0.93 (95% CI 0.88–0.97) versus 0.71 for the clinical-only model (all reported performance figures represent internal cross-validation only). SHAP analysis identified Δ MBF and Δ entropy at week 3 as the dominant features, with high bootstrap stability. Conclusions: Multi-parametric ultrasound radiomic kinetics integrated through a machine learning ensemble may provide an interpretable early-response biomarker for NAC in breast cancer, pending external validation. Full article

Ngueak Pla Mo is a Thai medicinal crude drug derived from the pharmacopoeial Acanthus species A. ebracteatus Vahl and A. ilicifolius L.; however, morphological similarity and the occurrence of non-pharmacopoeial substitutes such as A. montanus (Nees) T. Anderson may complicate authentication and quality control. This study aimed to develop an integrated molecular–chemical approach for differentiating pharmacopoeial Ngueak Pla Mo species from A. montanus. Twenty authenticated Acanthus samples were analyzed using ITS2 DNA barcoding, including nucleotide variation, pairwise genetic distance, barcode gap, haplotype network, phylogenetic analysis, and predicted ITS2 secondary structure. Representative samples were further examined by untargeted LC–QTOF/MS metabolite profiling combined with hierarchical clustering, PCA, PLS-DA, VIP analyses, fold-change evaluation, and specificity scoring. ITS2 analyses clearly separated A. montanus from A. ebracteatus and A. ilicifolius, supported by diagnostic sequence variation, positive barcode gaps, distinct haplotypes, phylogenetic clustering, and secondary-structure differences, whereas A. ebracteatus and A. ilicifolius could not be reliably differentiated from each other at the species level using ITS2. LC–QTOF/MS profiling revealed species-consistent metabolite patterns and prioritized gallic acid, catechol, 3,4-dihydroxybenzoic acid, trigonelline, and ursolic acid as preliminary candidate markers for A. montanus discrimination. These results indicate that combining ITS2 barcoding with metabolite profiling provides complementary evidence for Ngueak Pla Mo authentication and supports future quality-control development. Full article

Background: Asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous chronic airway disorders characterized by complex interactions among inflammation, immune dysregulation, environmental exposures, and tissue remodeling. Conventional clinical classifications based on symptoms, lung function, and exacerbation history often fail to fully capture the biological mechanisms underlying disease progression and therapeutic variability. Methods: This narrative review summarizes current evidence regarding the biological and clinical significance of YKL-40, mannose-binding lectin (MBL), and epigenetic remodeling in asthma and COPD, with particular emphasis on the inflammation–epigenetic axis and its potential role in disease phenotyping and precision medicine. Results: Available evidence suggests that YKL-40, MBL, and epigenetic signatures represent complementary biomarker layers reflecting tissue remodeling, innate immune variability, and cumulative inflammatory adaptation, respectively. Chronic inflammatory signaling, oxidative stress, and epigenetic remodeling may contribute to persistent molecular memory and phenotypic stabilization, providing a mechanistic framework for understanding disease heterogeneity and progression. Advances in multi-omics technologies, artificial intelligence, and machine learning are further supporting the development of integrated multimarker models. Conclusions: YKL-40, MBL, and epigenetic signatures should currently be considered complementary research variables rather than validated clinical tools. Their translation requires disease-specific assay standardization, prospective evaluation against prespecified outcomes, external validation, and evidence that biomarker-guided decisions improve patient care. Full article

This review examines the evolving role of muscle biopsy in the diagnosis of neuromuscular disorders in the era of modern genomic medicine. Historically the cornerstone of myopathy diagnosis, muscle biopsy enabled structural, histochemical, and ultrastructural characterization of muscle diseases. However, the introduction of next-generation sequencing and other genomic technologies has shifted the diagnostic paradigm, with genetic testing now serving as the preferred first-line approach for many hereditary myopathies due to its non-invasive nature and high diagnostic yield. However, muscle biopsy remains indispensable in the evaluation of inflammatory, toxic, metabolic, mitochondrial, and certain rare acquired myopathies. Biopsy is also valuable when genetic testing is inconclusive, particularly for interpreting variants of uncertain significance, through histopathological, immunohistochemical, and biochemical analyses. In certain disorders, diagnosis may rely primarily on biopsy findings. Emerging technologies, including RNA sequencing, transcriptomics, proteomics, spatial transcriptomics, and artificial intelligence-assisted pathology, are expanding the diagnostic value of muscle tissue beyond traditional morphological assessment. Rather than being replaced by genomic medicine, muscle biopsy is evolving into a complementary component of an integrated diagnostic strategy that combines clinical, pathological, and molecular data to improve diagnostic accuracy and guide precision medicine in neuromuscular disorders. Full article

Toad poison (ChanSu), a traditional animal-derived medicine, has long been used in East Asian medical systems for the treatment of inflammatory conditions and tumor-related disorders. While bufadienolides have been extensively investigated as its major bioactive constituents, the contribution of peptide components to its antitumor effects remains largely unexplored. Here, we identified protein-derived candidate antiproliferative peptides from toad poison using an integrated proteomics and bioinformatics-guided strategy. Proteomic analysis identified 135 proteins, from which 2117 peptide sequences were generated via in silico digestion with trypsin and pepsin. Subsequent multi-step screening using PeptideRanker, AntiCP, iACP, and ACPred yielded twelve candidate peptides with predicted anticancer activity. Network pharmacology analysis suggested their potential involvement in cancer-related targets and pathways. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) evaluation was subsequently used as a complementary assessment of drug-like and safety-related properties, further prioritizing four peptides for experimental validation, while molecular docking supported their interactions with key lung cancer-associated targets. In vitro assays demonstrated that three of the four prioritized peptides (WEAWN, NSQWG, and ACGVIGICQ) exhibited initial antiproliferative activity against human lung cancer A549 cells, though these findings should be interpreted with caution given the absence of a positive control in the MTT assay. This study provides preliminary evidence suggesting that protein-derived peptide candidates from toad poison may possess antiproliferative potential, representing an early systematic exploration of its previously unexplored peptidome as a source of candidate antiproliferative peptides warranting further pharmacological investigation. The integrated strategy presented here offers an efficient approach for the discovery of bioactive peptides from animal-derived traditional medicines. Full article

Volatile fingerprints provide useful information for characterizing Astragali Radix (AR), a food–medicine homologous plant material, but differences among wild, wild-simulated, and cultivated samples remain unclear. In this study, headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC–MS) and headspace gas chromatography–ion mobility spectrometry (HS-GC–IMS) were integrated with multivariate analysis and interpretable machine learning to characterize volatile profiles and identify candidate discriminatory compounds in 117 AR samples from different cultivation patterns. HS-SPME-GC–MS tentatively identified 29, 34, and 45 volatile compounds in wild, wild-simulated, and cultivated samples, respectively. Esters were the predominant class in all groups, although the relative abundance of esters and the overall chemical-class composition varied among cultivation patterns. HS-GC–IMS tentatively identified 57, 50, and 55 compounds, respectively, comprising mainly low-molecular-weight aldehydes, alcohols, and ketones and thereby providing complementary volatile fingerprint information. Partial least squares discriminant analysis (PLS-DA) showed that the volatile fingerprints captured cultivation-pattern-associated differences, with the HS-GC–IMS model showing clearer group separation. Random forest, support vector machine, and CatBoost models were further constructed using the HS-SPME-GC–MS profiling results. By integrating variable importance in projection (VIP) and SHapley Additive exPlanations (SHAP) values, γ-hexalactone, methyl eugenol, methyl (9Z,11E)-octadeca-9,11-dienoate, eugenol, and ethyl linoleate were selected as candidate discriminatory compounds. Based on the HS-GC–IMS results, 1-octen-3-one, pentyl acetate, (Z)-2-penten-1-ol, 2-heptanone, and the monomeric signal of 2-ethyl-6-methylpyrazine were also identified as candidate discriminatory compounds. These compounds may be related to fatty acid-derived metabolism, aromatic secondary metabolism, and terpenoid-related processes. The integration of two complementary volatile-analysis platforms with VIP- and SHAP-based interpretation provided broader coverage of volatile features and improved the interpretability of candidate-compound screening. These findings provide an interpretable analytical workflow and candidate discriminatory compounds that may support future rapid screening, cultivation-pattern authentication, and volatile-profile-based differentiation of AR, pending independent external validation. Full article

Recovery in elite athletes represents a critical determinant of performance and health outcomes. The gut microbiota has been proposed as a modulating factor for recovery through anti-inflammatory mechanisms, oxidative stress management, sleep regulation, and biosynthetic potential for essential micronutrients. This review examines the mechanisms linking gut microbiota composition and function to athletic recovery and critically evaluates the evidence supporting its application in sports medicine. Athletes appear to harbor a more enriched microbial biosynthetic potential, with substantially greater numbers of high-biological-impact synthases involved in the production of vitamins, amino acids, and bioactive metabolites. Short-chain fatty acids, particularly butyrate and propionate, have demonstrated anti-inflammatory effects in preclinical studies, with emerging evidence in humans. The gut–brain axis has been proposed to modulate recovery by regulating neurotransmitter production and controlling circadian rhythms. Sport-associated microbial signatures seem to reflect metabolic demands, with endurance athletes showing enrichment for Prevotella and Veillonella, while strength athletes tend to harbor higher levels of proteolytic bacteria. Probiotic interventions with multi-strain Lactobacillus and Bifidobacterium formulations have reported reductions in inflammatory markers, improvements in oxidative stress biomarkers, and enhanced sleep quality in small-scale randomized controlled trials involving athletic populations, and improvements in self-reported sleep quality in a controlled, non-randomized study in elite athletes. Optimizing gut microbiota composition and function offers a promising complementary strategy for enhancing recovery in elite athletes. Potential applications that require prospective validation include sport-specific probiotic interventions, nutritional strategies to enhance short-chain fatty acid production, and the integration of microbiota assessment with traditional recovery monitoring. Further research is needed to establish standardized protocols and identify predictive biomarkers of individual response to microbiota-targeted interventions. Full article

Background/Objectives: Post-stroke spasticity is a common and disabling complication that impairs functional recovery. Acupuncture is used as a complementary intervention in stroke rehabilitation, but evidence for specific techniques, including acupoint-to-acupoint penetrating acupuncture (AAPA), remains limited. This study evaluated the adjunctive effects and safety of AAPA applied to limb acupoints in patients with post-stroke spasticity receiving conventional care. Methods: A systematic review and meta-analysis of randomized controlled trials was conducted. Nine databases and five clinical trial registries were searched from inception to June 2026. Trials compared AAPA plus conventional care with conventional care alone. The primary outcome was post-treatment spasticity severity. Risk of bias was assessed using RoB 2, and evidence certainty using GRADE. Results: Sixteen studies involving 1170 participants were included. Adjunctive AAPA significantly reduced Modified Ashworth Scale scores (SMD = −0.91, 95% CI: −1.23 to −0.59). Motor function, gait, balance, activities of daily living, and neurological deficits were also improved. However, most studies had a high overall risk of bias, no trial used a sham acupuncture comparator, and substantial heterogeneity was observed for several outcomes. The certainty of evidence for all GRADE-assessed clinical outcomes was very low. Conclusions: The findings suggest possible add-on benefits of AAPA when used with conventional post-stroke care, but the current evidence should be interpreted cautiously and is insufficient to support definitive clinical recommendations. Rigorous multicenter trials in diverse rehabilitation settings with standardized outcomes, systematic safety assessment, and longer follow-up are needed. Full article

Background: Contemporary adults face fragmented schedules, sedentary digital work, cognitive load, logistical barriers, and unstable routines that can make conventional session-based exercise difficult to sustain. Exercise snacks, vigorous intermittent lifestyle physical activity (VILPA), movement breaks, low-volume high-intensity interval training (HIIT), workplace exercise, and digitally mediated physical activity may reflect a broader redesign of exercise for real-world lifestyles. Objective: To develop a conceptual framework for lifestyle-congruent exercise models: approaches that intentionally modify dose, timing, setting, delivery, autonomy, or routine integration to reduce lifestyle-related friction while preserving a plausible physiological or behavioral stimulus. Methods: This evidence-based narrative review purposively identified sources through targeted searches, citation tracking, and manual verification across exercise science, sedentary behavior, workplace health, behavioral medicine, and digital health. Sources were selected for conceptual relevance, model-family representation, evidence-type diversity, and contribution to framework development, and then charted by model family, population, context, exercise architecture, delivery, outcomes, and implementation features. No systematic protocol, formal risk-of-bias assessment, or certainty grading were applied. Results: Thirty-one sources informed the framework. Five design logics were identified: dose compression, temporal distribution, routine embedding, sedentary substitution, and delivery mediation. These logics show that brief or time-efficient models are not interchangeable; they differ in intentionality, context, behavioral demand, safety considerations, implementation logic, and dominant friction addressed. Conclusions: Lifestyle-congruent exercise models are complementary strategies, not replacements for structured aerobic and muscle-strengthening exercise. Their value lies in matching exercise architecture to lifestyle-related friction while supporting progression toward guideline-consistent activity. Future research should test safety, equity, scalability, and long-term maintenance across diverse populations. Full article