搜索结果：Perfect

Fluoroquinolone-resistant Escherichia coli is a major global clinical threat, particularly in low- and middle-income countries like Nigeria. However, the full genomic landscape, including the relative contributions of chromosomal mutations, plasmid-mediated resistance, and the role of high-risk clones, remains poorly characterized in this setting. This study aimed to define the genomic mechanisms, clonal distribution, and genotype-phenotype relationships of fluoroquinolone resistance in clinical E. coli isolates from Nigeria. A cross-sectional study of 107 clinical E. coli isolates was conducted. Phenotypic susceptibility to ciprofloxacin and nalidixic acid was determined using VITEK 2 and broth microdilution. Whole-genome sequencing was performed, and analysis included detection of quinolone resistance determining region (QRDR) mutations (gyrA, parC, parE) and plasmid-mediated quinolone resistance (PMQR) genes, multilocus sequence typing (MLST), and phylogenetic analysis. Statistical associations were evaluated using chi-squared tests or Fisher's exact tests. Ciprofloxacin non-susceptibility was high at 86.0%. Resistance was primarily driven by a conserved chromosomal mutation profile; the combination of gyrA S83L, gyrA D87N, and parC S80I was present in 85 isolates and was associated with ciprofloxacin non-susceptibility in all affected isolates in this cohort. Isolates with only gyrA mutations were resistant to nalidixic acid but susceptible to ciprofloxacin, consistent with a stepwise resistance pathway. In this cohort, the triple QRDR signature (gyrA S83L + gyrA D87N/Y + parC S80I) was a perfect positive predictor of ciprofloxacin non-susceptibility (85/85; 100%). The ST131 lineage dominated, accounting for 21.5% of isolates and universally carrying the complete triple QRDR profile; notably, no ST131 isolate carried a PMQR determinant. Plasmid-mediated quinolone resistance (PMQR) genes were detected in 15.0% of isolates but were not independently associated with ciprofloxacin non-susceptibility in this cohort in the absence of concomitant QRDR mutations. Efflux pump genes were ubiquitous and non-predictive. Notably, six isolates, all from urine, were non-susceptible (R/I) despite lacking all known QRDR and PMQR determinants, pointing to uncharacterized mechanisms. In a multivariable logistic regression model that included ST131 status, PMQR carriage, and parE mutation status, ST131 was associated with ciprofloxacin non-susceptibility (adjusted OR 5.96, 95% CI 1.21-29.4, p = 0.028), whereas PMQR carriage was not (adjusted OR 0.94, 95% CI 0.18-4.85, p = 0.94). The triple QRDR signature was not included in this model because it perfectly predicted ciprofloxacin non-susceptibility in this cohort. Resistance patterns varied by clinical source, with the highest burden in bloodstream and wound infections. This stepwise hierarchy from first-step gyrA mutations to the classic triple QRDR profile is summarised in the graphical abstract, Fig. 1. Fluoroquinolone resistance in Nigerian clinical E. coli is predominantly driven by chromosomal QRDR mutations within successful clones like ST131. PMQR genes and efflux pumps appeared to play a supplementary role rather than being independent drivers of ciprofloxacin resistance in this cohort. These data support prioritising key QRDR mutations in genomic reporting and local stewardship decisions, while the QRDR-negative resistant urine isolates require further investigation.

Accurate assessment of burn depth and total body surface area (TBSA) is critical for clinical decision-making; however, it remains subjective and prone to interobserver variability. Multimodal large language models (MLLMs) are increasingly encountered in clinical contexts, but whether these systems can reliably assess burn images remains unclear. We evaluated four MLLMs (GPT-5.4 Pro, Grok 4.1, Gemini 3.1 Pro, and Claude Opus 4.6) on 50 clinical burn photographs using a repeated-inference design with five independent runs per model. Burn depth classification was assessed in numeric and text-based formats, alongside ordinal TBSA estimation. Performance varied across the models, with burn depth accuracy ranging from 34.0 ± 6.5% to 76.4 ± 6.8% and TBSA accuracy from 32.8 ± 9.4% to 68.4 ± 3.3%. Inter-run reliability (Fleiss' κ) ranged from slight (κ = 0.171) to almost perfect (κ = 0.916), demonstrating response variability not captured by single-query evaluations. Notably, no model combined high accuracy and high reliability, indicating a dissociation between performance and consistency. All models showed a tendency toward overestimation of burn depth, including assignment of fourth-degree burns despite their absence in the dataset. Error direction analysis revealed model-specific and task-dependent biases, including opposing patterns within the same model. Internal consistency between numeric and text classifications was near-perfect (99.6-100%), indicating format-invariant but systematically biased outputs. These findings demonstrate that MLLM performance is characterized by stochastic response instability invisible to single-query evaluations. Such inconsistency for identical inputs represents a fundamental limitation for workflows requiring consistent outputs across repeated evaluations.

To evaluate the agreement and diagnostic performance of the Node Reporting and Data System 1.0 (Node-RADS) for preoperative lymph node staging in cervical cancer across readers with different experience levels. This retrospective study enrolled 439 consecutive cervical cancer patients who underwent preoperative MRI and lymph node dissection. Target nodes were pre-specified by a most experienced consultant radiologist to unify the assessment objects. Four readers (two senior with 9-11 years of experience, two junior with 3-5 years of experience) independently assigned Node-RADS scores, blinded to histopathology. Inter-reader agreement and between-group agreement were assessed using weighted and Cohen's kappa. Diagnostic performance was evaluated against histopathology as reference standard. Senior readers achieved near-perfect agreement for Node-RADS scores (k&#x2009;=&#x2009;0.988), nodal status (k&#x2009;=&#x2009;0.959) and all individual morphological parameters (k&#x2009;=&#x2009;0.847-0.967). Junior readers showed moderate to substantial agreement (k&#x2009;=&#x2009;0.554-0.754). Although junior readers requiring consensus more frequently (7.1% vs. 1.4%, p&#x2009;<&#x2009;0.01), the between-group agreement for nodal status was substantial (k&#x2009;=&#x2009;0.783). For nodal metastasis detection, senior readers demonstrated higher diagnostic performance (AUC 0.868; sensitivity 76.4%; specificity 97.3%) compared to junior readers (AUC 0.758; sensitivity 54.6%; specificity 97.0%), and both groups presented favorable diagnostic efficacy overall. Inter-reader agreement for nodal status was almost perfect among senior readers and substantial among junior readers. Diagnostic performance was slightly better in the senior group, suggesting an influence of reader experience.

Congenital umbilical anomalies (umbilical cord hernia, larger umbilical hernias, and epithelialized omphaloceles) present a significant challenge for surgeons in achieving perfect reconstruction. About 10 years ago, we came up with the idea of forming six cutaneous flaps for reconstruction, resulting in what can be described as the perfect umbilicus. We demonstrate the application of this technique in three different cases of umbilical anomalies. The described technique for forming a neo-umbilicus using six cutaneous flaps is very simple and precise. Its application achieves excellent esthetic results without complications.

This study investigates the portrayal and age-related stereotypes of older adult characters in popular Chinese films. Content analysis of 100 films (2000-2024) yielded 305 older adult characters. Findings show older adults remain underrepresented, with a pronounced gender imbalance favoring older males. Contrary to prior research, positive portrayals predominate; over 90% of characters showed positive stereotypes like Tidy, Experienced, Face-conscious, and Polite. Tidy was the most frequent positive stereotype, while Despondent was the most common negative one, differing from Western stereotypes of The Perfect Grandparents and Shrew/Curmudgeon. Gender differences occurred in positive stereotypes: older men were more often Experienced and Hard-working, whereas older women were more likely Noncompetitive and The Perfect Grandparent. Negative stereotypes showed no gender differences. These findings contribute to understanding the evolving media construction of ageing in contemporary popular Chinese films and hold important implications for future research on age stereotypes and the cultural politics of media representation.

New food databases increasingly provide biochemical information not yet captured in standard food composition databases (FCDs). To enable precision nutrition, new methods are needed to map foods to these FCDs. We sought to provide real-world ground truth (benchmark) datasets and evaluate the use of large language models (LLMs) to match foods reported in dietary data with foods in FCDs. Two ground truth (benchmark) datasets were developed. ASA24-to-FooDB included a large FCD (9,910 entries) with many similar or perfect matches. NHANES-to-DFG2 included a small FCD (256 entries) with imperfect matches or "No Match" (46.9%). Matching methods tested included fuzzy matching, TF-IDF, semantic embedding, and LLMs. Food text description mapping using similarity scores from semantic embedding performed better on both ground truth datasets (87.8% accuracy, ASA24-to-FooDB; 48.0% accuracy, NHANES-to-DFG2) than fuzzy matching or TF-IDF. LLMs performed worse on ASA24-to-FooDB when given the entire FCD, but better on NHANES-to-DFG2 (62.6% accuracy). For foods where a correct match exists, semantic similarity yielded top K accuracies of 85% at k=5, 95% at k=10 for ASA24-to-FooDB and 96% at k=5, 98% at k=10 for NHANES-to-DFG2. A hybrid approach using semantic embeddings to select the top K matches to prompt LLMs yielded overall accuracies of 90.7% on ASA24-to-FooDB and 65.4% on NHANES-to-DFG2. An investigation of different prompt strategies and model sizes demonstrated that simpler prompts worked better for larger LLMs while smaller LLMs needed detailed instructions. To assist nutrition scientists, the best strategy (semantic mapping + LLM reranking) was implemented in an application: FoodMapper (https://foodmapper.app/). To match food text descriptions to FCDs, identifying top matches using semantic similarity followed by an LLM to choose from among those matches or "no match" resulted in the highest accuracy. FoodMapper provides users with the best solution in a user-friendly interface that facilitates manual review.

Rolling circle amplification (RCA) is a powerful isothermal nucleic acid amplification technique, yet its specificity is often compromised because padlock probes can be circularized even with imperfectly matched targets, leading to false-positive signals. Herein, we report a strand displacement-assisted FEN1 cleavage strategy to substantially improve the specificity of RCA. A dumbbell-shaped padlock probe is designed to generate dual 5' flaps only upon perfect hybridization with the target. Flap endonuclease 1 (FEN1) specifically recognizes the three-base overlap structure and cleaves the 5' flaps, enabling stringent single-base mismatch discrimination over a recognition length exceeding 23 base pairs. After FEN1 cleavage, the padlock is circularized by T4 DNA ligase, followed by RCA triggered by primer-conjugated magnetic beads. The RCA products form G-quadruplex structures that bind thioflavin T (ThT) for fluorescence readout. The method achieves excellent sensitivity for breast cancer-related biomarkers, with detection limits of 0.61 fM for hsa-miR-2682 and 1.13 fM for hsa_circ_0131242, along with high specificity (single-base resolution), good reproducibility (CV < 5%), and satisfactory recovery (95.1-101.5%) in serum. Clinical validation using 15 breast cancer patient samples and 15 healthy controls shows that the method reliably recapitulates differential expression of hsa_circ_0131242, with results highly consistent with RT-qPCR. By overcoming the inherent specificity limitation of conventional RCA, this FEN1-assisted, strand displacement-enhanced strategy provides a sensitive, reliable, and versatile platform for RNA biomarker analysis, holding great promise for early diagnosis of breast cancer and other diseases.

Clinically, X-linked hypohidrotic ectodermal dysplasia is identified by its classic triad of hypohidrosis, hypotrichosis, and oligodontia. Nevertheless, the true threat to patient survival often stems from respiratory complications that extend beyond these obvious ectodermal traits. Mechanistically, ectodysplasin A (EDA) variants impair skin appendages and respiratory submucosal glands, undermining mucociliary clearance. This vulnerability, exacerbated by thermoregulatory instability from sweat gland dysfunction, establishes a pathological environment prone to severe infections, leaving infants at high risk for life-threatening fungal pneumonia and sepsis. Despite high early-life mortality, this potential lethality is frequently overlooked in pediatrics because glandular defects are nearly invisible on standard imaging. The proband was a male infant aged approximately 74 days. After birth, he repeatedly developed a fever and was hospitalized. Imaging confirmed pulmonary infection, and pathogen examination revealed Fusarium, Saccharomyces cerevisiae, and Achromobacter xylosoxidans. Given the patient's typical clinical features of ectodermal dysplasia, whole exome sequencing was performed with consent. Results showed a novel hemizygous frameshift variant, c.916delC (p.Gln306ArgfsTer2), in EDA. Subsequently, Sanger sequencing was performed on the direct relatives of the proband, and detailed clinical phenotype assessment and medical history collection were conducted for 17 members spanning four generations of the pedigree. Lineage analysis showed that transmission of this variant exhibited perfect cosegregation with the disease phenotype in the family, consistent with X-linked recessive inheritance. Unfortunately, the proband died at 2 years and 6 months from severe pneumonia. This study identified a novel pathogenic EDA variant c.916delC, expanding the pathogenic variation spectrum of this gene. Through detailed family case reports and combined with imaging and pathogen evidence, we observe and suggest that underdeveloped respiratory mucosal glands and skin heat dissipation disorders may be an important pathological basis for fatal pneumonia and multiple infections in infants and young children with X-linked hypohidrotic ectodermal dysplasia. This discovery emphasizes the necessity of increasing clinical awareness of respiratory system involvement in such children, and suggests that adopting active temperature management, airway care, and reasonable anti-infection strategies in the early stages of diagnosis and treatment has important clinical reference value for improving the prognosis of children.

Echinococcus multilocularis, which causes alveolar echinococcosis, can infect a wide range of hosts. Increasing interactions among wildlife, domestic animals, and humans may enhance the transmission risk in endemic areas. Surveillance of E. multilocularis in definitive hosts has relied on the post-mortem examination of the small intestine using the sedimentation and counting technique, with a recent shift toward non-invasive methods targeting fecal samples. However, host identification based solely on visual inspection of feces is often unreliable. Existing PCR-based methods are limited by complexity, low resolution, or a narrow range of target species. In this study, we developed a multiplex PCR assay targeting the mitochondrial 16S rRNA gene for simultaneous identification of 10 host species and evaluated its performance against a reference PCR assay. A total of 114 fecal samples, visually considered as fox-derived, were collected from roadsides in three areas in Hokkaido, Japan. Animal species were successfully identified in 106 samples (93.0%) using the newly developed multiplex PCR assay. Overall, foxes were the most common (74.6%), followed by cats (12.3%), dogs (5.3%), and raccoons (1.8%). The new assay showed almost perfect agreement with the reference method (&#x3ba;&#x202f;=&#x202f;0.94; 95% CI: 0.87-1; n&#x202f;=&#x202f;114). Molecular identification revealed that 20.6% of samples were not derived from foxes, indicating that visual inspection is prone to identification errors. PCR screening detected E. multilocularis DNA in 34.2% of all samples. The positivity rate was 41.2% in foxes and 28.6% in cats. These findings highlight the importance of accurate host identification for reliable E. multilocularis surveillance. The developed multiplex PCR assay provides a rapid and robust approach to improve epidemiology accuracy and support effective control strategies.

Clinical neurosensory testing (NST) is reliable for grading trigeminal nerve injuries but is not well suited to large-scale or remote follow-up. The 12-item patient-reported Medical Research Council Sensory Questionnaire (MRCS-Q), which mirrors the clinical Medical Research Council scale in plain language suitable for electronic administration, was therefore developed and prospectively validated. Ten patients with post&#x2011;traumatic trigeminal neuropathy and ten healthy volunteers completed the questionnaire and the Douleur Neuropathique 4 (DN4), while a blinded examiner scored subjects using NST; questionnaires were repeated after 2 weeks. Psychometric performance was assessed with Cronbach's &#x3b1;, intraclass correlation coefficients (ICCs), Spearman correlation coefficients, and receiver operating characteristic analysis. Questionnaire totals correlated strongly with clinical scale grades (0.83; P&#xa0;<&#xa0;0.001) and with questionnaire&#x2011;derived grade (0.96; P&#xa0;<&#xa0;0.001). Internal consistency was good (&#x3b1; =&#xa0;0.72) and test-retest reliability excellent (ICC = 0.96). Higher questionnaire scores were associated with lower DN4 scores (-0.72; P&#xa0;<&#xa0;0.001) and with less self&#x2011;reported numbness (-0.88; P&#xa0;<&#xa0;0.001). Diagnostic accuracy for neuropathy was very good with an area under the curve of 0.90; a threshold of &#x2264;5 yielded 0.90 sensitivity and 1.00 specificity, whereas DN4 showed perfect specificity but only 0.30 sensitivity. The patient&#x2011;reported questionnaire offers a rapid, reliable and valid measure of trigeminal neurosensory function that could support electronic screening, and remote outcome assessment, pending multicenter confirmation.

This study addresses the challenge of accurately predicting the physicochemical properties of arthritis drugs using simple graph-theoretic descriptors and evaluates whether combining degree-based topological indices with modern machine learning can outperform traditional linear QSPR models. Nine classical degree-based topological indices (including reformulated Zagreb indices, augmented Zagreb index, hyper-Zagreb index, forgotten index, symmetric division degree index, and inverse sum Zagreb index) were computed for 50 structurally diverse arthritis drugs ranging from NSAIDs (ibuprofen and diclofenac) and COX-2 inhibitors (celecoxib) to disease-modifying agents (methotrexate) and immunomodulators with experimental property values (boiling point, melting point, critical pressure, molar refractivity, topological polar surface area, and calculated LogP) obtained from ChemDraw and PubChem. Using these indices as input features, linear regression, Random Forest, and XGBoost models were developed and compared. XGBoost consistently outperformed the other methods across all properties, achieving for molar refractivity a mean absolute error (MAE) of 0.80787, a root-mean-square error (RMSE) of 1.13352, and coefficient of determination (r 2 = 0.9945); for boiling point, RMSE = 16.22 and r 2 = 0.9866; for melting point, RMSE = 25.86 and r 2 = 0.9450; for critical pressure, RMSE = 1.176 and r 2 = 0.9833; for topological polar surface area, RMSE = 4.38 and r 2 = 0.9762; and for CLogP, RMSE = 0.586 and r 2 = 0.8857. Random Forest also performed well but with slightly higher errors, while linear regression showed moderate to strong correlations for boiling point, melting point, molar refractivity, and tPSA but failed to capture nonlinear structure-property relationships. The novelty of this work lies in the first systematic integration of nine degree-based topological indices with advanced ensemble learning (XGBoost and Random Forest) for QSPR modeling of a large, diverse arthritis drug data set, demonstrating that simple connectivity measures&#xe5f8;when paired with nonlinear machine learning&#xe5f8;can achieve near-perfect predictive accuracy for key properties, offering a low-cost, computationally efficient framework for drug design and virtual screening.

Maxillary sinus-related adverse events are clinically relevant in posterior maxillary implant therapy, but their reporting patterns in public postmarket surveillance data remain incompletely characterized. This retrospective text-mining study analyzed FDA Manufacturer and User Facility Device Experience (MAUDE) reports from 2015 to 2025 involving endosseous dental implants with product code DZE. Device records were linked to FOITEXT (MAUDE narrative text) records and Master Event fields by MDR_REPORT_KEY. Sinus-related narratives were identified using staged keyword rules, refined into high-specificity candidates, classified into event categories, assessed for duplicate and template-like text, and validated using independent blinded dual review of a stratified quality-control sample. Among 3,386,630 unique DZE reports, the workflow retained 6,386 high-specificity maxillary sinus-related candidates. Independent blinded dual review of a 449-record stratified validation sample showed substantial agreement for inclusion status (Cohen's &#x3ba;&#x2009;=&#x2009;0.778) and almost perfect agreement for event-category assignment (Cohen's &#x3ba;&#x2009;=&#x2009;0.907). The conservative consensus-confirmed positive predictive value (PPV) was 96.88% (435/449). Sinus membrane perforation narratives were the predominant rule-based report category, but this pattern should be interpreted as a reporting and documentation pattern rather than a true clinical frequency. Unique-text sensitivity analysis reduced repeated narratives but did not materially change the category-level pattern. This study characterizes maxillary sinus-related reporting patterns in a passive postmarket surveillance database. The findings highlight the value and limitations of transparent text-mining workflows for implant-related adverse event surveillance and should not be interpreted as clinical incidence, comparative risk, manufacturer performance, or causality.

In business, politics, and life, folk wisdom encourages people to aim for above-average results, but not to let the perfect be the enemy of the good. Here, we mathematically formalize and extend this folk wisdom. We model a time-limited search for strategies having uncertain rewards. At each time step, the searcher is either satisfied with their current reward or continues searching. We prove that the optimal satisfaction threshold is both finite and strictly larger than the mean of available rewards-matching folk wisdom. This result is robust to search costs, unless they are high enough to prohibit all search. We show that being too ambitious has a higher expected cost than being too cautious. We show that the optimal satisfaction threshold increases if the search time is longer, or if the reward distribution is rugged (i.e., has low autocorrelation) or left-skewed. The skewness result reveals counterintuitive contrasts between optimal ambition and optimal risk-taking. We show that using upward social comparison to assess the reward landscape substantially harms expected performance. We show how these insights can be applied qualitatively to real-world settings, using examples from entrepreneurship, economic policy, political campaigns, online dating, and college admissions. We discuss implications of several possible extensions of our model, including intelligent search, reward landscape uncertainty, and risk aversion.

This study investigated whether field-based intermittent tests performed under fatigued conditions better predict Olympic cross-country mountain biking (XCO-MTB) performance, whether prior prolonged exercise reduces power output during these tests, and whether the ability to maintain power output during intermittent tests under fatigue distinguishes competitive level in mountain bikers. Twenty-five male XCO-MTB athletes were tested under "fresh" and fatigued conditions in randomized order, separated by 72&#x2009;h. Within each condition, participants performed three field-based intermittent tests with work: recovery formats of 30&#x2009;s:15&#x2009;s (30/15), 10&#x2009;s:20&#x2009;s (10/20), and 3&#x2009;min:2&#x2009;min (3/2), in randomized order and separated by 24&#x2009;h. In the fatigued condition, each intermittent test was immediately preceded by a 140-min fatigue protocol that included repeated efforts at 105%-110% of critical power. Participants were classified as high-performance (HP) or low-performance (LP) based on XCO-MTB individual time-trial (ITT) performance, assessed 72&#x2009;h after the last test session. All intermittent tests showed large to nearly perfect correlations with XCO-MTB ITT performance (n&#x2009;=&#x2009;24; r&#x2009;=&#x2009;-0.53 to -0.95; p&#x2009;=&#x2009;0.007 to p&#x2009;<&#x2009;0.001), with stronger associations under fatigued conditions. The fatigued 10/20 test expressed relative to body mass was the strongest predictor, explaining 89% of performance variance. Power output decreased across all three tests after the fatigue protocol (n&#x2009;=&#x2009;25; all p&#x2009;<&#x2009;0.001), with greater declines in the LP group (&#x2248;15%-20%) than in the HP group (&#x2248;6%-10%; p&#x2009;=&#x2009;0.008 to p&#x2009;<&#x2009;0.001). In conclusion, these findings suggest that the ability to sustain power output during repeated intermittent efforts under fatigue is relevant to XCO-MTB ITT performance and competitive level.

Traditional visual methods used in posture analysis are limited by subjectivity and variability, whereas computer vision systems provide precise geometric measurements but require technical expertise and specialized resources. Large language models like ChatGPT offer an accessible, low-cost alternative with human-like interpretive abilities and potential educational value. This study aimed to examine the agreement between ChatGPT and expert physiotherapists in standardized photographic posture assessments. This cross-sectional comparative study included 39 young adults with at least one visible postural deviation. The sampling frame consisted of individuals preliminarily evaluated during a posture assessment assignment by physiotherapy students. Standardized anterior, posterior, and lateral photographs were taken under controlled conditions. Two physiotherapists independently assessed posture using a seven-region Posture Analysis Form, and the same anonymized photographs were evaluated by ChatGPT-5.1 (multimodal version, web interface, 15-16 November 2025) using a standardized prompt. Inter-rater agreement between physiotherapists was excellent (&#x3ba;&#x2009;=&#x2009;0.84-0.94). Agreement between physiotherapists and ChatGPT ranged from moderate to excellent. Trunk (&#x3ba;&#x2009;=&#x2009;0.85) and knee alignment (&#x3ba;&#x2009;=&#x2009;0.83) showed almost perfect agreement, while head-neck position showed substantial agreement (&#x3ba;&#x2009;=&#x2009;0.67). In contrast, scapular (&#x3ba;&#x2009;=&#x2009;0.51), shoulder girdle (&#x3ba;&#x2009;=&#x2009;0.47), pelvic (&#x3ba;&#x2009;=&#x2009;0.47), and foot alignment (&#x3ba;&#x2009;=&#x2009;0.43) exhibited moderate agreement. Percentage agreement ranged from 64.10% to 92.31%. This study suggested that ChatGPT shows high agreement with physiotherapists in regions with clearly observable postural deviations, while its reliability decreases in areas requiring finer angular discrimination. The findings further indicate that the model may serve as a supportive tool, particularly for assessing trunk, knee, and head-neck alignment.