Anthropometric measures of obesity in patients with knee joint pathology: Body surface area versus body mass index.

BACKGROUND: Obesity is quantified using body mass index. Body surface area may provide a superior and more anthropometric method of quantifying obesity in patients with musculoskeletal knee disease. This study compares the effect of weight, height, age and gender on body mass index and body surface area in a population with orthopaedic knee disease. METHODS: An observational cohort study was conducted of patients presenting with musculoskeletal knee disease. Associations between body mass index, body surface area, age, gender, height, weight and operative versus non-operative management were analysed. RESULTS: A total of 151 patients were included. Body surface area was more strongly correlated to weight than body mass index (r = 0.98, p < 0.001 versus r = 0.84, p < 0.001). Body surface area also reflects height which body mass index under presents (r = 0.65, p < 0.001 versus r = -0.08, p = 0.35). Body mass index and body surface area were correlated with one another (r = 0.70, p < 0.001). Age was inversely correlated with body surface area (r = -0.20, p = 0.013) but not body mass index (r = 0.05, p = 0.585). Body mass index did not differ between males and females (30.1 versus 30.9, p = 0.37); however, BSA scores were significantly higher in males than females (2.11 versus 1.91, p < 0.001). Neither body surface area nor body mass index scores influenced operative versus non-operative treatment. CONCLUSION: Body surface area could be a useful alternative to body mass index when considering obesity in patients with musculoskeletal knee pathology. Body surface area better reflects the effects of height, weight, age and gender than body mass index.

Evaluation of comorbidity scoring systems in patients undergoing knee arthroplasty.

BACKGROUND: Ageing populations are increasing the demand for knee arthroplasty. Concurrently, the prevalence of medical comorbidities are rising too. The Self-Administered Comorbidity Questionnaire was developed to provide a patient's assessment of their own comorbidities whereas the American Society of Anesthesiologists grades and the Charlson Comorbidity Index utilise clinical evaluation to objectively measure perioperative morbidity and mortality risk. The primary aim of this study was to compare Self-Administered Comorbidity Questionnaire scores with American Society of Anesthesiologists grades and Charlson Comorbidity Index scores. The secondary aim was to compare Self-Administered Comorbidity Questionnaire scores with knee outcome scores. METHODS: A single centre observational cohort study of patients with knee osteoarthritis undergoing elective knee arthroplasty. Preoperative evaluation included Self-Administered Comorbidity Questionnaire scores, American Society of Anesthesiologists grades, Charlson Comorbidity Index scores and validated patient-reported outcome measures specific to knee surgery. RESULTS: A total of 141 patients were included in this study. Self-Administered Comorbidity Questionnaire scores were directly correlated with American Society of Anesthesiologists grade (rho = 0.37, p < 0.001) and Charlson Comorbidity Index scores (rho = 0.19, p = 0.047). Individual American Society of Anesthesiologists grades had significantly different Self-Administered Comorbidity Questionnaire scores (p = 0.001). Self-Administered Comorbidity Questionnaire scores were specifically associated with hypertension, ischaemic heart disease, chronic obstructive pulmonary disease and the total number of comorbidities, but American Society of Anesthesiologists and Charlson Comorbidity Index scores were associated with more comorbidities. Overall, Self-Administered Comorbidity Questionnaire scores were inversely correlated with patient-reported outcome measure scores. CONCLUSION: Self-Administered Comorbidity Questionnaire scores are associated with increasing comorbidity in patients with symptomatic knee osteoarthritis; however, American Society of Anesthesiologists grades and Charlson Comorbidity Index scores had stronger and more abundant associations with comorbidities and patient-reported outcome measure scores. Self-Administered Comorbidity Questionnaires may complement but not replace current objective assessments of comorbidity when evaluating perioperative risk for knee arthroplasty.

Auditory cues modulate the short timescale dynamics of STN activity during stepping in Parkinson's disease.

BACKGROUND: Gait impairment has a major impact on quality of life in patients with Parkinson's disease (PD). It is believed that basal ganglia oscillatory activity at ß frequencies (15-30 Hz) may contribute to gait impairment, but the precise dynamics of this oscillatory activity during gait remain unclear. Additionally, auditory cues are known to lead to improvements in gait kinematics in PD. If the neurophysiological mechanisms of this cueing effect were better understood they could be leveraged to treat gait impairments using adaptive Deep Brain Stimulation (aDBS) technologies. OBJECTIVE: We aimed to characterize the dynamics of subthalamic nucleus (STN) oscillatory activity during stepping movements in PD and to establish the neurophysiological mechanisms by which auditory cues modulate gait. METHODS: We studied STN local field potentials (LFPs) in eight PD patients while they performed stepping movements. Hidden Markov Models (HMMs) were used to discover transient states of spectral activity that occurred during stepping with and without auditory cues. RESULTS: The occurrence of low and high ß bursts was suppressed during and after auditory cues. This manifested as a decrease in their fractional occupancy and state lifetimes. Interestingly, α transients showed the opposite effect, with fractional occupancy and state lifetimes increasing during and after auditory cues. CONCLUSIONS: We show that STN oscillatory activity in the α and ß frequency bands are differentially modulated by gait-promoting oscillatory cues. These findings suggest that the enhancement of α rhythms may be an approach for ameliorating gait impairments in PD.

Evaluation of 3D C-Arm Fluoroscopy versus Diagnostic CT for Deep Brain Stimulation Stereotactic Registration and Post-Operative Lead Localization.

INTRODUCTION: DBS efficacy depends on accuracy. CT-MRI fusion is established for both stereotactic registration and electrode placement verification. The desire to streamline DBS workflows, reduce operative time, and minimize patient transfers has increased interest in portable imaging modalities such as the Medtronic O-arm® and mobile CT. However, these remain expensive and bulky. 3D C-arm fluoroscopy (3DXT) units are a smaller and less costly alternative, albeit incompatible with traditional frame-based localization and without useful soft tissue resolution. We aimed to compare fusion of 3DXT and CT with pre-operative MRI to evaluate if 3DXT-MRI fusion alone is sufficient for accurate registration and reliable targeting verification. We further assess DBS targeting accuracy using a 3DXT workflow and compare radiation dosimetry between modalities. METHODS: Patients underwent robot-assisted DBS implantation using a workflow incorporating 3DXT which we describe. Two intra-operative 3DXT spins were performed for registration and accuracy verification followed by conventional CT post-operatively. Post-operative 3DXT and CT images were independently fused to the same pre-operative MRI sequence and co-ordinates generated for comparison. Registration accuracy was compared to 15 consecutive controls who underwent CT-based registration. Radial targeting accuracy was calculated and radiation dosimetry recorded. RESULTS: Data were obtained from 29 leads in 15 consecutive patients. 3DXT registration accuracy was significantly superior to CT with mean error 0.22 ± 0.03 mm (p < 0.0001). Mean Euclidean electrode tip position variation for CT to MRI versus 3DXT to MRI fusion was 0.62 ± 0.40 mm (range 0.0 mm-1.7 mm). In comparison, direct CT to 3DXT fusion showed electrode tip Euclidean variance of 0.23 ± 0.09 mm. Mean radial targeting accuracy assessed on 3DXT was 0.97 ± 0.54 mm versus 1.15 ± 0.55 mm on CT with differences insignificant (p = 0.30). Mean patient radiation doses were around 80% lower with 3DXT versus CT (p < 0.0001). DISCUSSION: Mobile 3D C-arm fluoroscopy can be safely incorporated into DBS workflows for both registration and lead verification. For registration, the limited field of view requires the use of frameless transient fiducials and is highly accurate. For lead position verification based on MRI co-registration, we estimate there is around a 0.4 mm discrepancy between lead position seen on 3DXT versus CT when corrected for brain shift. This is similar to that described in O-arm® or mobile CT series. For units where logistical or financial considerations preclude the acquisition of a cone beam CT or mobile CT scanner, our data support portable 3D C-arm fluoroscopy as an acceptable alternative with significantly lower radiation exposure.

Blunted perception of breathlessness in three cases of low grade insular-glioma.

Better understanding of breathlessness perception addresses an unmet clinical need for more effective treatments for intractable dyspnoea, a prevalent symptom of multiple medical conditions. The insular-cortex is predominantly activated in brain-imaging studies of dyspnoea, but its precise role remains unclear. We measured experimentally-induced hypercapnic air-hunger in three insular-glioma patients before and after surgical resection. Tests involved one-minute increments in inspired CO2, raising end-tidal PCO2 to 7.5 mmHg above baseline (38.5 ± 5.7 mmHg), whilst ventilation was constrained (10.7 ± 2.3 L/min). Patients rated air-hunger on a visual analogue scale (VAS). Patients had lower stimulus-response (2.8 ± 2 vs. 11 ± 4 %VAS/mmHg; p = 0.004), but similar threshold (40.5 ± 3.9 vs. 43.2 ± 5.1 mmHg), compared to healthy individuals. Volunteered comments implicated diminished affective valence. After surgical resection; sensitivity increased in one patient, decreased in another, and other was unable to tolerate the ventilatory limit before any increase in inspired CO2.We suggest that functional insular-cortex is essential to register breathlessness unpleasantness and could be targeted with neuromodulation in chronically-breathless patients. Neurological patients with insula involvement should be monitored for blunted breathlessness to inform clinical management.

Spatiotemporal signal space separation for regions of interest: Application for extracting neuromagnetic responses evoked by deep brain stimulation.

Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources may spatially extend (known as source leakage) into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large-scale cortical networks. In this technical report, we develop a novel denoising approach for suppressing the leakage of interference source activity into the activity representing a brain region of interest. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We apply this denoising approach to reconstruct simulated evoked response topographies to deep brain stimulation (DBS) in a phantom recording. We highlight the advantages of our approach compared to the benchmark-spatiotemporal signal space separation-and show that it can more accurately reveal brain stimulation-evoked response topographies. Finally, we apply our method to MEG recordings from a single patient with Parkinson's disease, to reveal early cortical-evoked responses to DBS of the subthalamic nucleus.

Near-infrared spectroscopy as a novel method of ex vivo bladder cancer tissue characterisation.

OBJECTIVE: To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. PATIENTS AND METHODS: A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. RESULTS: A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. CONCLUSIONS: This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.

Identification of 2 Distinct Boundaries Distinguishes Critical From Noncritical Isthmuses in Ablating Atypical Atrial Flutter.

BACKGROUND: Atypical atrial flutters often involve complex circuits. Classic methods of identifying ablation targets, including detailed electroanatomical mapping and entrainment within a well-defined isthmus, may not always be sufficient to allow the critical isthmus to be delineated and ablated, with flutter termination and prevention of reinduction. OBJECTIVES: This study sought a systematic method to classify conduction barriers and isthmuses as critical or noncritical that would improve understanding and ablation success. We also sought a construct unifying single- and dual-loop re-entry. Re-entrant circuits are bounded on 2 sides, although these are not consistently identified. We hypothesized 2 distinct critical boundaries, and a critical isthmus could be consistently defined without requiring entrainment, and ablation connecting these 2 boundaries would terminate tachycardia. METHODS: Activation maps were created electroanatomically. Conduction barriers were classified as noncritical barriers or critical boundaries. Critical boundaries showed sequential activation around the barrier, spanning ≥90% of the cycle length. Noncritical barriers showed nonsequential, parallel, or colliding activation or <90% of the cycle length. Only tissue separating the 2 critical boundaries defined a critical isthmus (CI); all others were considered noncritical. The effect of ablation across a CI was assessed. RESULTS: Complete maps were obtained in 128 cases in 121 patients (28 atypical right atrial, 100 left atrial). In all cases, 2 distinct critical boundaries were identified. Ablation across a CI connecting these critical boundaries terminated tachycardia in 123 of 128 cases (96.1%). Failures were due to inability to achieve block across the isthmus. CONCLUSIONS: Activation mapping of atypical atrial flutter allows consistent identification of 2 critical boundaries. Successful ablation connecting the 2 critical boundaries reliably results in termination of atypical atrial flutter.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation.

BACKGROUND AND OBJECTIVES: Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers. MATERIALS AND METHODS: We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation. RESULTS: High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment. CONCLUSIONS: High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming.

Changing Surgical Culture Through Surgical Education: Introduction to the PACTS Trial.

The Provider Awareness and Cultural dexterity Toolkit for Surgeons (PACTS) curriculum was developed to improve surgical resident cultural dexterity, with the goal of promoting health equity by developing cognitive skills to adapt to individual patients' needs to ensure personal, patient-centered surgical care through structured educational interventions for surgical residents. Funded by the National Institute of Health (NIH)'s National Institute on Minority Health and Health Disparities, PACTS addresses surgical disparities in patient care by incorporating varied educational interventions, with investigation of both traditional and nontraditional educational outcomes such as patient-reported and clinical outcomes, across multiple hospitals and regions. The unique attributes of this multicenter, multiphased research trial will not only impact future surgical education research, but hopefully improve how surgeons learn nontechnical skills that modernize surgical culture and surgical care. The present perspective piece serves as an introduction to this multifaceted surgical education trial, highlighting the rationale for the study and critical curricular components such as key stakeholders from multiple institutions, multimodal learning and feedback, and diverse educational outcomes.

Deep brain stimulation for chronic pain: a systematic review and meta-analysis.

Background: Deep brain stimulation (DBS) has shown promise in effectively treating chronic pain. This study aimed to assess the efficacy of DBS in this context. Methods: We conducted a systematic literature search using PubMed, Scopus, and Web of Science, following the PRISMA guidelines. A well-constructed search strategy was utilized. Our literature search identified two groups of subjects: one group underwent DBS specifically for chronic pain treatment (DBS-P), while the second group received DBS for other indications (DBS-O), such as Parkinson's disease or dystonia, with pain perception investigated as a secondary outcome in this population. Meta-analysis was performed using R version 4.2.3 software. Heterogeneity was assessed using the tau^2 and I^2 indices, and Cochran's Q-test was conducted. Results: The analysis included 966 patients in 43 original research studies with chronic pain who underwent DBS (340 for DBS-P and 625 for DBS-O). Subgroup analysis revealed that DBS-P exhibited a significant effect on chronic pain relief, with a standardized mean difference (SMD) of 1.65 and a 95% confidence interval (CI) of [1.31; 2.00]. Significant heterogeneity was observed among the studies, with an I^2 value of 85.8%. However, no significant difference was found between DBS-P and DBS-O subgroups. Subgroup analyses based on study design, age, pain diseases, and brain targets demonstrated varying levels of evidence for the effectiveness of DBS across different subgroups. Additionally, meta-regression analyses showed no significant relationship between age or pain duration and DBS effectiveness for chronic pain. Conclusion: These findings significantly contribute to the expanding body of knowledge regarding the utility of DBS in the management of chronic pain. The study underscores the importance of conducting further research to enhance treatment outcomes and elucidate patient-specific factors that are associated with treatment response. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=428442, identifier CRD42023428442.

Point-of-care detection of fibrosis in liver transplant surgery using near-infrared spectroscopy and machine learning.

Introduction: Visual assessment and imaging of the donor liver are inaccurate in predicting fibrosis and remain surrogates for histopathology. We demonstrate that 3-s scans using a handheld near-infrared-spectroscopy (NIRS) instrument can identify and quantify fibrosis in fresh human liver samples. Methods: We undertook NIRS scans on 107 samples from 27 patients, 88 from 23 patients with liver disease, and 19 from four organ donors. Results: Liver disease patients had a median immature fibrosis of 40% (interquartile range [IQR] 20-60) and mature fibrosis of 30% (10%-50%) on histopathology. The organ donor livers had a median fibrosis (both mature and immature) of 10% (IQR 5%-15%). Using machine learning, this study detected presence of cirrhosis and METAVIR grade of fibrosis with a classification accuracy of 96.3% and 97.2%, precision of 96.3% and 97.0%, recall of 96.3% and 97.2%, specificity of 95.4% and 98.0% and area under receiver operator curve of 0.977 and 0.999, respectively. Using partial-least square regression machine learning, this study predicted the percentage of both immature (R 2 = 0.842) and mature (R 2 = 0.837) with a low margin of error (root mean square of error of 9.76% and 7.96%, respectively). Conclusion: This study demonstrates that a point-of-care NIRS instrument can accurately detect, quantify and classify liver fibrosis using machine learning.

Readiness of Medical Students to Care for Diverse Patients: A Validated Assessment of Cross-Cultural Preparedness, Skills, and Curriculum.

Introduction: Effective cross-cultural care is foundational for mitigating health inequities and providing high-quality care to diverse populations. However, medical school teaching practices vary widely, and learners have limited opportunities to develop these critical skills. To understand the current state of cross-cultural education and to identify potential opportunities for improvement, we disseminated a validated survey instrument among medical students at a single institution. Methods: Learners across 4 years of medical school participated in the cross-cultural care assessment, using a tool previously validated with resident physicians and modified for medical students. The survey assessed medical student perspectives on (1) preparedness, (2) skillfulness, and (3) educational curriculum and learning environment. Cross-sectional data were analyzed by class year, comparing trends between school years. Results: Of 700 possible survey responses, we received 260 (37% response rate). Fourth-year students had significantly higher scores than first-year students (p<0.05) for 7 of 12 preparedness items and 4 of 9 skillfulness items. Less than 50% of students indicated readiness to deliver cross-cultural care by their fourth year in 9 of 12 preparedness items and 6 of 9 skillfulness items. Respondents identified inadequate cross-cultural education as the primary barrier. Discussion: Medical students reported a lack of readiness to provide cross-cultural care, with self-assessed deficiencies persisting through the fourth year of medical school. Medical educators can use data from the cross-cultural care survey to longitudinally assess students and enhance curricular exposures where deficiencies exist. Optimizing cross-cultural education has the potential to improve the learning environment and overall patient care.

Radiation induces long-term muscle fibrosis and promotes a fibrotic phenotype in fibro-adipogenic progenitors.

BACKGROUND: Radiation-induced muscle pathology, characterized by muscle atrophy and fibrotic tissue accumulation, is the most common debilitating late effect of therapeutic radiation exposure particularly in juvenile cancer survivors. In healthy muscle, fibro/adipogenic progenitors (FAPs) are required for muscle maintenance and regeneration, while in muscle pathology FAPs are precursors for exacerbated extracellular matrix deposition. However, the role of FAPs in radiation-induced muscle pathology has not previously been explored. METHODS: Four-week-old Male CBA or C57Bl/6J mice received a single dose (16 Gy) of irradiation (IR) to a single hindlimb with the shielded contralateral limb (CLTR) serving as a non-IR control. Mice were sacrificed 3, 7, 14 (acute IR response), and 56 days post-IR (long-term IR response). Changes in skeletal muscle morphology, myofibre composition, muscle niche cellular dynamics, DNA damage, proliferation, mitochondrial respiration, and metabolism and changes in progenitor cell fate where assessed. RESULTS: Juvenile radiation exposure resulted in smaller myofibre cross-sectional area, particularly in type I and IIA myofibres (P < 0.05) and reduced the proportion of type I myofibres (P < 0.05). Skeletal muscle fibrosis (P < 0.05) was evident at 56 days post-IR. The IR-limb had fewer endothelial cells (P < 0.05) and fibro-adipogenic progenitors (FAPs) (P < 0.05) at 56 days post-IR. Fewer muscle satellite (stem) cells were detected at 3 and 56 days in the IR-limb (P < 0.05). IR induced FAP senescence (P < 0.05), increased their fibrogenic differentiation (P < 0.01), and promoted their glycolytic metabolism. Further, IR altered the FAP secretome in a manner that impaired muscle satellite (stem) cell differentiation (P < 0.05) and fusion (P < 0.05). CONCLUSIONS: Our study suggests that following juvenile radiation exposure, FAPs contribute to long-term skeletal muscle atrophy and fibrosis. These findings provide rationale for investigating FAP-targeted therapies to ameliorate the negative late effects of radiation exposure in skeletal muscle.

Towards a point-of-care multimodal spectroscopy instrument for the evaluation of human cardiac tissue.

To demonstrate that point-of-care multimodal spectroscopy using Near-Infrared (NIR) and Raman Spectroscopy (RS) can be used to diagnose human heart tissue. We generated 105 spectroscopic scans, which comprised 4 NIR and 3 RS scans per sample to generate a "multimodal spectroscopic scan" (MSS) for each heart, done across 15 patients, 5 each from the dilated cardiomyopathy (DCM), Ischaemic Heart Disease (IHD) and Normal pathologies. Each of the MSS scans was undertaken in 3 s. Data were entered into machine learning (ML) algorithms to assess accuracy of MSS in diagnosing tissue type. The median age was 50 years (IQR 49-52) for IHD, 47 (IQR 45-50) for DCM and 36 (IQR 33-52) for healthy patients (p = 0.35), 60% of which were male. MSS identified key differences in IHD, DCM and normal heart samples in regions typically associated with fibrosis and collagen (NIR wavenumbers: 1433, 1509, 1581, 1689 and 1725 nm; RS wavelengths: 1658, 1450 and 1330 cm-1). In principal component (PC) analyses, these differences explained 99.2% of the variation in 4 PCs for NIR, 81.6% in 10 PCs for Raman, and 99.0% in 26 PCs for multimodal spectroscopic signatures. Using a stack machine learning algorithm with combined NIR and Raman data, our model had a precision of 96.9%, recall of 96.6%, specificity of 98.2% and Area Under Curve (AUC) of 0.989 (Table 1). NIR and Raman modalities alone had similar levels of precision at 94.4% and 89.8% respectively (Table 1). MSS combined with ML showed accuracy of 90% for detecting dilated cardiomyopathy, 100% for ischaemic heart disease and 100% for diagnosing healthy tissue. Multimodal spectroscopic signatures, based on NIR and Raman spectroscopy, could provide cardiac tissue scans in 3-s to aid accurate diagnoses of fibrosis in IHD, DCM and normal hearts. Table 1 Machine learning performance metrics for validation data sets of (a) Near-Infrared (NIR), (b) Raman and (c and d) multimodal data using logistic regression (LR), stochastic gradient descent (SGD) and support vector machines (SVM), with combined "stack" (LR + SGD + SVM) AUC Precision Recall Specificity (a) NIR model  Logistic regression 0.980 0.944 0.933 0.967  SGD 0.550 0.281 0.400 0.700  SVM 0.840 0.806 0.800 0.900  Stack 0.933 0.794 0.800 0.900 (b) Raman model  Logistic regression 0.985 0.940 0.929 0.960  SGD 0.892 0.869 0.857 0.932  SVM 0.992 0.940 0.929 0.960  Stack 0.954 0.869 0.857 0.932 (c) MSS: multimodal (NIR + Raman) to detect DCM vs. IHD vs. normal patients  Logistic regression 0.975 0.841 0.828 0.917  SGD 0.847 0.803 0.793 0.899  SVM 0.971 0.853 0.828 0.917  Stack 0.961 0.853 0.828 0.917 (d) MSS: multimodal (NIR + Raman) to detect pathological vs. normal patients  Logistic regression 0.961 0.969 0.966 0.984  SGD 0.944 0.967 0.966 0.923  SVM 1.000 1.000 1.000 1.000  Stack 1.000 0.944 0.931 0.969 Bold values indicate values obtained from the stack algorithm and used for analyses.

Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation.

Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.

Generative and predictive neural networks for the design of functional RNA molecules.

RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence and structural properties of an RNA molecule and its ability to perform specific functions often necessitates extensive experimental screening of candidate sequences. Here we present a generalized neural network architecture that utilizes the sequence and structure of RNA molecules (SANDSTORM) to inform functional predictions. We demonstrate that this approach achieves state-of-the-art performance across several distinct RNA prediction tasks, while learning interpretable abstractions of RNA secondary structure. We paired these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of novel mRNA 5' untranslated regions and toehold switch riboregulators exhibiting a predetermined fitness. This approach enabled the design of novel toehold switches with a 43-fold increase in experimentally characterized dynamic range compared to those designed using classic thermodynamic algorithms. SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of diagnostic and therapeutic RNA molecules with improved function.