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Does future-oriented imagery rescripting increase willingness to carry out a social anxiety-related behavioral experiment? An extended replication.

BACKGROUND AND OBJECTIVES: Mental images of threat are common in social anxiety disorder and could impede exposure to fear-relevant situations. Landkroon et al. (2022) found that imagery rescripting of anticipated future threat, compared to no-task, increases willingness of non-clinical individuals to conduct a social anxiety-related behavioral experiment. The aim of this two-day preregistered extended replication study was to examine whether the effects persist beyond the intervention session by scheduling the behavioral experiment 1-7 days after the intervention. METHODS: On Day 1, 60 pre-screened participants were asked to design a behavioral experiment to test an idiosyncratic negative belief about a feared social situation. They were then randomly assigned to imagery rescripting (focused on their worst feared outcome of the behavioral experiment) or no-task. Participants' willingness to do the behavioral experiment and their threat beliefs was measured. On Day 2, they were asked to carry out the behavioral experiment. RESULTS: The imagery rescripting group, compared to the control group, did not show increased willingness or compliance to do the behavioral experiment on Day 1 or 2. Furthermore, the imagery rescripting did not lead to greater reductions in threat beliefs on either day. LIMITATIONS: The quality of the imagery rescripting intervention was not assessed, and given the brief nature of the intervention, any effects may have dissipated before participants decided whether to carry out the behavioral experiment. CONCLUSIONS: There was no evidence that imagery rescripting leads to changes in willingness or compliance to do a fear-relevant behavioral experiment. More research is needed to examine interventions that can enhance exposure in socially anxious people.

Humans

Structured Visualization for Laparoscopic Skill Acquisition:A Randomized Controlled Study.

OBJECTIVE: To evaluate whether structured visualization can support acquisition of basic laparoscopic skills during simulation training and whether this approach can achieve outcomes comparable to repeated physical practice. DESIGN: Prospective randomized comparative study. SETTING: Simulation-based laparoscopic skills training at a university-affiliated teaching center. PARTICIPANTS: Fifty laparoscopy-naive medical students were randomly assigned to a laparoscopic practice group or a visualization group. The laparoscopic practice group performed a validated Gynecological Endoscopic Surgical Education and Assessment (GESEA) Laparoscopic Skills Training and Testing (LASTT) hand-eye coordination task 7 consecutive times. The visualization group performed the same task physically on attempts 1, 4, and 7, while attempts 2, 3, 5, and 6 consisted of guided visualization. Each attempt lasted up to 2 minutes, and performance was scored as the number of correctly placed rings (range 0-12). RESULTS: Baseline performance was comparable between groups (2.92&#x202f;&#xb1;&#x202f;2.14&#x202f;vs 2.88&#x202f;&#xb1;&#x202f;1.72; p&#x202f;=&#x202f;0.94). Both groups improved significantly over time (p&#x202f;<&#x202f;0.001). No statistically significant between-group differences were found on the 4th attempt (6.52&#x202f;&#xb1;&#x202f;3.25&#x202f;vs 5.76&#x202f;&#xb1;&#x202f;2.57; p&#x202f;=&#x202f;0.48) or 7th attempt (8.24&#x202f;&#xb1;&#x202f;2.86&#x202f;vs 7.44&#x202f;&#xb1;&#x202f;2.99; p&#x202f;=&#x202f;0.39). The final physical performance of the visualization group was significantly better than the 3rd physical attempt of the laparoscopic practice group (p&#x202f;=&#x202f;0.025). CONCLUSIONS: Structured visualization may support early laparoscopic skill acquisition and achieve short-term outcomes comparable to repeated hands-on simulator training. Visualization should be considered an adjunct, rather than a replacement, for physical practice in simulation-based laparoscopic education.

Laparoscopy

Immersive virtual reality-assisted anatomy training improves endotracheal intubation performance in simulation: a randomized controlled trial among Chinese non-anesthesiology residents.

INTRODUCTION: This study aimed to compare immersive virtual reality (IVR)-assisted versus conventional anatomy training for teaching endotracheal intubation (ETI) to novice non-anesthesiology residents enrolled in China's Standardized Residency Training program. METHODS: A total of 90 non-anesthesiology residents without prior ETI experience were randomly assigned to either an IVR group receiving IVR-assisted anatomy training (n&#x2009;=&#x2009;45) or a control group receiving conventional anatomy training (n&#x2009;=&#x2009;45). All participants underwent a standardized teaching protocol. The primary endpoint was residents' ETI performance on a simulator, assessed using both the Global Rating Scale (GRS) and a task-specific checklist. The secondary endpoints included changes in written multiple-choice question (MCQ) scores and residents' evaluations of the course. RESULTS: In practical ETI assessments on a manikin, the IVR group achieved significantly higher scores on the task-specific checklist than the control group (90.34&#x2009;&#xb1;&#x2009;2.89 vs. 87.20&#x2009;&#xb1;&#x2009;3.29; p&#x2009;<&#x2009;0.001), whereas GRS scores were comparable between groups. Both groups showed significant post-training improvement in knowledge scores (p&#x2009;<&#x2009;0.001), with the IVR group showing a greater gain in theoretical knowledge (54.0% vs. 36.3%; p&#x2009;<&#x2009;0.001). Participants in the IVR group also expressed a stronger preference for their training method (80.8%) and reported higher levels of motivation, confidence, and enjoyment (all p&#x2009;<&#x2009;0.05). CONCLUSION: IVR-assisted anatomy training enhances the effectiveness of ETI training for novice non-anesthesiology residents, offering an interactive, engaging, and reproducible approach within China's Standardized Residency Training framework.

Humans

Catecholaminergic Contributions to Inhibitory Control Following Physical Fatigue: Behavioral and Neurophysiological Findings.

Acute physical fatigue can impair cognitive control, yet its underlying neurochemical mechanisms remain unclear. This study investigated whether catecholaminergic modulation influences behavioral and neural markers of inhibitory control following physical fatigue. Eighteen healthy, recreationally active adults (9 males, 9 females; 23.4&#xa0;&#xb1;&#xa0;2.2&#xa0;years) completed a randomized, triple-blind, placebo-controlled crossover study. On separate visits, participants received methylphenidate (MPH; 20&#xa0;mg; a dopamine and noradrenaline reuptake inhibitor), reboxetine (REB; 8&#xa0;mg; a noradrenaline reuptake inhibitor), or placebo. Physical fatigue was induced by repeated bilateral leg extensions to task failure. Cognitive performance was assessed before and after physical fatigue using a Go/No-Go task with electroencephalographic recording. Behavioral outcomes included reaction time and accuracy, while event-related potentials measured neural stages of response execution and inhibition (N2 and P3). Mixed-effects models were used for statistical analysis. For No-Go trials, a significant MPH&#xa0;&#xd7;&#xa0;Time interaction was observed for accuracy (p&#xa0;=&#xa0;0.008), with improved post-fatigue performance following MPH administration (p&#xa0;=&#xa0;0.048). At the neural level, MPH was associated with shorter fronto-central No-Go N2 latency (p&#xa0;=&#xa0;0.038) and altered fatigue-related changes in No-Go P3 latency (p&#xa0;=&#xa0;0.047). REB did not produce comparable behavioral or neural effects. These findings provide pharmacological evidence that catecholaminergic mechanisms contribute to inhibitory control following physical fatigue. The differential effects of MPH and REB suggest that selective noradrenergic enhancement alone is insufficient to maintain inhibitory control following physical fatigue. Instead, the findings implicate broader&#xa0;dopaminergic and noradrenergic mechanisms, potentially involving alterations in the temporal dynamics of inhibitory processing. TRIAL REGISTRATION: (G095422N and identifier NCT05880342).

Adult

Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases.

PURPOSE: To evaluate whether a cornea-specialized large language model (LLM) enhanced with retrieval-augmented generation (RAG) improves clinicians' diagnostic and management accuracy in complex corneal cases compared to a general-purpose GPT-4o model and unaided clinician performance. METHODS: This prospective, randomized, masked evaluation study involved three cornea trainees who each independently reviewed 39 real-world corneal cases under three experimental conditions: unaided, GPT-4o-assisted, and assisted by a cornea-specialized GPT-4o model. The cornea-specialized model was constructed by embedding over 200 publicly available Wikipedia articles into GPT-4o's RAG framework. Participants provided open-ended diagnoses and selected the next-step management options (multiple choice). They were allowed up to three GPT-4o queries per case, and the AI-assisted arms were randomized to minimize bias. Accuracy for both tasks was compared against expert reference standards using McNemar's test. RESULTS: Diagnostic accuracy was 48.7%, 20.5%, and 38.5% unaided, improving to 69.2%, 46.2%, and 59.0% with general GPT-4o (p<0.04). The cornea-specialized GPT-4o further improved accuracy to 71.8%, 48.7%, and 74.4%, with improvements over unaided performance for all clinicians (p<0.01). For next-step decisions, unaided accuracy was 76.9%, 87.2%, and 59.0%. With the specialized model, Ophthalmologist 3 improved to 71.8% (p<0.05), Ophthalmologist 1 remained high at 82.1%, and Ophthalmologist 2 declined to 64.1% (p<0.05). CONCLUSIONS: A cornea-specialized LLM enhanced with RAG improved diagnostic accuracy in complex corneal cases, particularly among clinicians with lower baseline performance. Effects on management accuracy were inconsistent. Future studies should explore the use of open-ended management tasks and examine whether smaller, curated retrieval corpora yield better model performance.

Humans

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis.&#xa0;A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST&#x2009;+&#x2009;AI for prediction model studies.&#xa0;Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST&#x2009;+&#x2009;AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection.&#xa0;AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

Game changer? Cognitive-motor effects of VR exergaming compared to video-based training.

BACKGROUND/OBJECTIVE: Virtual reality (VR) exergaming enhances several cognitive domains through multisensory engagement. Acute cognitive benefits of VR are established, but evidence for direct comparisons with non-immersive controls is limited. This study aimed to determine whether VR exercise provides additional cognitive and cognitive-motor benefits beyond a matched non-immersive active stick-fight video (SFV) intervention, and whether effects persist after training. METHODS: In this randomized quasi-experimental study, N&#x2009;=&#x2009;55 healthy adults (VR: n&#x2009;=&#x2009;30; SFV: n&#x2009;=&#x2009;25; 25.5&#x2009;&#xb1;&#x2009;7.1&#x2009;years; 41.8% female) completed an 8-week program (2&#x2009;&#xd7;&#x2009;30&#x2009;min/week), of VR or SFV matched in movement patterns, frequency, intensity and duration. Measurements included reaction time (RT), Stroop Test (versions 1-3), Letter Cancellation Test (LCT), Trail Making Test (TMT), Trail Walking Test (TWT) and Fitts task (difficulty level 1-4). Data were analyzed using mixed-design ANOVAs. RESULTS: Improvements were observed in Stroop reading (F(1,53) = 14.84, p < .001, &#x3b7;2 = 0.219), Stroop inhibition (F(1,53) = 10.99, p = .002, &#x3b7;2 = 0.172), and LCT (F(1,53) = 4.57, p = .037, &#x3b7;2 = 0.079). A time&#x2009;&#xd7;&#x2009;group interaction was found for TMT (F(1,53) = 6.55, p = .031, &#x3b7;2 = 0.110), indicating greater changes following VR training. Both groups improved cognitive-motor performance (TWT: F(1,25) = 55.32, p < .001, &#x3b7;2 = 0.689; Fitts3: F(1,53) = 44.97, p < .001, &#x3b7;2 = 0.459), with greater gains for VR in Fitts3 (p = .006). CONCLUSION(S): Eight weeks of VR and SFV enhanced cognitive and cognitive-motor performance. VR provided domain-specific advantages in executive function, but these effects were not uniformly persistent. SFV sustained more improvements in real-world-relevant cognitive-motor tasks.

Humans

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d&#x2009;=&#x2009;2.381&#xa0;mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44&#xa0;mm (95% CI, 4.02-6.86&#xa0;mm; p&#x2009;=&#x2009;2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p&#x2009;=&#x2009;5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p&#x2009;=&#x2009;0.26) or cognitive workload via the NASA-Task Load Index (p&#x2009;=&#x2009;0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures

Targeting cortico-striatal-amygdalar networks via theta-band frontoparietal synchronization in opioid use disorder: a randomized tACS-fMRI Trial.

Theta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. Sixty male participants with OUD were randomized to receive 20&#x2009;min of active or sham 6&#x2009;Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using time&#x2009;&#xd7;&#x2009;group interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. (1) A significant Time&#x2009;&#xd7;&#x2009;Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected &#x3b1;&#x2009;=&#x2009;0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement (&#x3b2;&#x2009;=&#x2009;2.63, p=&#x2009;0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum (&#x3b2;&#x2009;=&#x2009;1.99, p=&#x2009;0.037) and left medial amygdala (&#x3b2;&#x2009;=&#x2009;1.97, p=&#x2009;0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r&#x2009;=&#x2009;0.43, p=&#x2009;0.02). Together, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction.

Humans

Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.

BACKGROUND: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce. METHODS: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD. RESULTS: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.70, -0.19]; FDR-p&#xa0;=&#xa0;0.003) and verbal memory (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.72, -0.18]; FDR-p&#xa0;=&#xa0;0.003). Significant time &#xd7; group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances. CONCLUSIONS: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.

Humans

Clinical efficacy and brain mechanism characteristics of guide chi and regulate spirit tuina therapy in the treatment of post-stroke walking dysfunction: A randomized controlled trial based on fNIRS.

BACKGROUND: This study aims to preliminarily evaluate the role of Guide Chi and Regulate Spirit(GCRS) Tuina in enhancing walking function in post-stroke patients with walking dysfunction; secondly, by using functional near-infrared spectroscopy (fNIRS), it investigates the effect of GCRS Tuina on the restoration of brain function in this patient population. METHODS: Participants in the control group received 4-week rehabilitation treatment, while those in the Combined Tuina Group (CTG) additionally received GCRS Tuina therapy for another 4 weeks on this basis. Functional Ambulation Category (FAC), Fugl - Meyer Assessment Scale for Lower Extremity Motor Function (FMA - LE), and Modified Barthel Index (MBI) were evaluated at the baseline and after 4 treatment weeks. A gait and motion analysis system was used to measure step length, stride, walking speed, and step frequency. FNIRS was used to measure the resting-state functional connectivity(FC) strength, as well as the &#x3b2; - value and HbO2 concentration mean during the walking task. RESULTS: A total of 60 participants completed the randomized, and 53 completed the trial and entered the statistical analysis. Compared with the Single Rehabilitation Group(SRG), the CTG group had higher FAC, FMA-LE, and MBI scores after 4 weeks. After the treatment course, the standardized step length, stride, walking speed, and step frequency of the CTG were higher than SRG. At the Region of Interest(ROI) level, the CTG exhibited 13 inter-ROI FC strengths that were higher than SRG, and the differences could survive the FDR correction (PFDR<0.05). Under the walking task, the CTG group had higher &#x3b2; values in 18 channels and higher Oxyhemoglobin(HbO2) concentrations in 19 channels than the SRG (PFDR <0.05). CONCLUSION: GCRS Tuina therapy can significantly improve patients' walking function, enhance lower limb motor ability and daily living ability. It can improve walking efficiency. Tuina can significantly increase the FC and enhance the activation levels and HbO2 concentrations. The stimulation of Tuina may help reconstruct the brain's motor control network, restore impaired motor function, promote the occurrence of neural plasticity, strengthen the neural circuits in the cognitive-motor-sensory cortex to improve walking function. TRIAL REGISTRATION: This study has been registered with the International Traditional Medicine Clinical Trial Registry (ITMCTR2024000654).

Humans

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology

Standardized visual overlays enhance laparoscopic instruction: A mixed-methods evaluation.

Effective communication during laparoscopic procedures is frequently undermined by spatial disorientation and inconsistent terminology between instructors and trainees. This study examined whether standardized visual overlays on endoscopic monitors could enhance communication and learning. We conducted a three-phase mixed-methods study: qualitative observation of 20 laparoscopic teaching cases; a randomized trial of 63 second-year medical students assigned to control, clock, or alphanumeric grid (AG) overlays during three trials of a standardized transfer task; and intraoperative implementation in 44 cases (30 AG, 14 clock) with post-case surveys and qualitative feedback. In simulation, the clock overlay produced the fastest completion times, whereas the AG yielded the lowest error scores, and both overlays outperformed the control. Intraoperatively, the AG was rated higher than the clock for communication clarity, spatial orientation, perceived operative efficiency, and trainee confidence. Standardized visual overlays, particularly the AG, appear to support intraoperative teaching by providing a shared spatial frame of reference.

Laparoscopy

Human-Centered Workspace Optimization: A 2 &#xd7; 2 Factorial Study of Adjustable Furniture and Indoor Environmental Quality.

Small workspaces function as integrated systems, yet ergonomic furniture and indoor environmental conditions are usually evaluated separately. A six-site, assessor-blinded, randomized 2 &#xd7; 2 factorial controlled study was conducted of two multicomponent packages-adjustable furniture and optimized indoor environmental quality (IEQ)-among 240 office workers for four weeks. Each group included 60 participants. Overall comfort in week 4 was highest for both packages (5.62 &#xb1; 0.53 versus 3.99 &#xb1; 0.60 with fixed furniture and basic IEQ). In a site-adjusted factorial model with HC3 robust standard errors, the adjustable-furniture effect was 0.86 points (95% confidence interval [CI], 0.62-1.09), the optimized-IEQ effect was 0.34 points (95% CI, 0.12-0.55), and their interaction was 0.44 points (95% CI, 0.14-0.74). Adjustable furniture improved postural comfort and reduced neck and lower back discomfort; optimized IEQ improved environmental comfort; both packages improved perceived productivity, satisfaction, and fatigue. The task-accuracy interaction did not remain significant after false-discovery-rate adjustment, and exploratory mediation and spline analyses did not support indirect or nonlinear effects. These results support coordinated ergonomic and environmental implementation while preserving distinct outcome pathways.

Interior Design and Furnishings

Workplace Safety Champions: Strengthening safety culture through nurse engagement.

Workplace violence is a growing concern in health care, disproportionately affecting frontline nurses and nursing assistants. Despite high prevalence, underreporting remains a barrier to effective prevention and response. This article describes the development, implementation, and outcomes of a Workplace Safety Champion program designed to increase reporting of violent incidents and strengthen a culture of safety. A multidisciplinary task force developed an evidence-based Workplace Safety Champion course that emphasizes de-escalation strategies, reporting processes, and staff support. Champions were appointed across inpatient and emergency units and integrated into a hospital-wide Workplace Safety Champion Council. Program evaluation used course completion data and posttraining surveys. The organizational goal of having at least one trained champion in 90% of inpatient and emergency units was exceeded, with 98% of units represented (N = 93 champions). More than 85% of learners reported intent to change their response to workplace violence, and 90% endorsed improved knowledge of resources and de-escalation strategies. The Workplace Safety Champion program successfully improved staff awareness, reporting, and engagement in workplace violence prevention. Embedding champions across units can serve as a sustainable strategy to strengthen safety culture and support frontline health care workers.

Humans

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence

Longitudinal Neurocognitive Changes for Patients With Hematologic Malignancies Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review With Structured Narrative Synthesis.

OBJECTIVES: Neurocognitive changes in hematological malignancies (HM) and as a sequela of hematopoietic stem cell transplantation (HSCT) remain under-recognized. These changes may substantially affect patients' quality of life. Therefore, this review systematically evaluated longitudinal neurocognitive changes in patients with HM undergoing HSCT. METHODS: Following PRISMA guidelines, PubMed, Scopus, and CINAHL were searched on October 30, 2025. Longitudinal studies assessing neurocognitive changes in patients with HM undergoing HSCT, with or without healthy controls, were included. Risk of bias was assessed using an adapted National Institutes of Health quality assessment tool for before-after studies. Effect sizes with 95% confidence intervals were calculated to quantify changes in neurocognitive performance. RESULTS: Nine of 2012 studies met the inclusion criteria, with overall moderate study quality. Improvements may occur post-HSCT; however, allogeneic HSCT and myeloablative conditioning were main risk factors identified for persistent cognitive decline. In line with white matter damage, executive function and attention/processing speed impairments likely represent core deficits, which may affect other cognitive impairments. Post-HSCT changes depend on task characteristics, cognitive load, and conditioning intensity. CONCLUSIONS: Future research should emphasize regular neurocognitive assessment to guide cognitive rehabilitation, implement pre-transplant cognitive rehabilitation strategies to mitigate post-HSCT cognitive decline, and enhance treatment outcomes.

Humans