Surface atom knockout for the active site exposure of alloy catalyst.

The fine regulation of catalysts by the atomic-level removal of inactive atoms can promote the active site exposure for performance enhancement, whereas suffering from the difficulty in controllably removing atoms using current micro/nano-scale material fabrication technologies. Here, we developed a surface atom knockout method to promote the active site exposure in an alloy catalyst. Taking Cu3Pd alloy as an example, it refers to assemble a battery using Cu3Pd and Zn as cathode and anode, the charge process of which proceeds at about 1.1 V, equal to the theoretical potential difference between Cu2+/Cu and Zn2+/Zn, suggesting the electricity-driven dissolution of Cu atoms. The precise knockout of Cu atoms is confirmed by the linear relationship between the amount of the removed Cu atoms and the battery cumulative specific capacity, which is attributed to the inherent atom-electron-capacity correspondence. We observed the surface atom knockout process at different stages and studied the evolution of the chemical environment. The alloy catalyst achieves a higher current density for oxygen reduction reaction compared to the original alloy and Pt/C. This work provides an atomic fabrication method for material synthesis and regulation toward the wide applications in catalysis, energy, and others.

Intrinsic Self-Trapped Excitons in Graphitic Carbon Nitride.

Graphitic carbon nitrides (g-C3N4) as low-cost, chemically stable, and ecofriendly layered semiconductors have attracted rapidly growing interest in optoelectronics and photocatalysis. However, the nature of photoexcited carriers in g-C3N4 is still controversial, and an independent charge-carrier picture based on the band theory is commonly adopted. Here, by performing transient spectroscopy studies, we show characteristics of self-trapped excitons (STEs) in g-C3N4 nanosheets including broad trapped exciton-induced absorption, picosecond exciton trapping without saturation at high photoexcitation density, and transient STE-induced stimulated emissions. These features, together with the ultrafast exciton trapping polarization memory, strongly suggest that STEs intrinsically define the nature of the photoexcited states in g-C3N4. These observations provide new insights into the fundamental photophysics of carbon nitrides, which may enlighten novel designs to boost energy conversion efficiency.

NH3 Electrosynthesis from N2 Molecules: Progresses, Challenges, and Future Perspectives.

Green ammonia (NH3), made by using renewable electricity to split nearly limitless nitrogen (N2) molecules, is a vital platform molecule and an ideal fuel to drive the sustainable development of human society without carbon dioxide emission. The NH3 electrosynthesis field currently faces the dilemma of low yield rate and efficiency; however, decoupling the overlapping issues of this area and providing guidelines for its development directions are not trivial because it involves complex reaction process and multidisciplinary entries (for example, electrochemistry, catalysis, interfaces, processes, etc.). In this Perspective, we introduce a classification scheme for NH3 electrosynthesis based on the reaction process, namely, direct (N2 reduction reaction) and indirect electrosynthesis (Li-mediated/plasma-enabled NH3 electrosynthesis). This categorization allows us to finely decouple the complicated reaction pathways and identify the specific rate-determining steps/bottleneck issues for each synthesis approach such as N2 activation, H2 evolution side reaction, solid-electrolyte interphase engineering, plasma process, etc. We then present a detailed overview of the latest progresses on solving these core issues in terms of the whole electrochemical system covering the electrocatalysts, electrodes, electrolytes, electrolyzers, etc. Finally, we discuss the research focuses and the promising strategies for the development of NH3 electrosynthesis in the future with a multiscale perspective of atomistic mechanisms, nanoscale electrocatalysts, microscale electrodes/interfaces, and macroscale electrolyzers/processes. It is expected that this Perspective will provide the readers with an in-depth understanding of the bottleneck issues and insightful guidance on designing the efficient NH3 electrosynthesis systems.

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which highlights the importance of providing screening for high-risk populations. Purpose To evaluate the effectiveness of dual-energy x-ray absorptiometry (DXA) screening in high-risk patients with osteoporosis identified by an artificial intelligence (AI) model using chest radiographs. Materials and Methods This randomized controlled trial conducted at an academic medical center included participants 40 years of age or older who had undergone chest radiography between January and December 2022 without a history of DXA examination. High-risk participants identified with the AI-enabled chest radiographs were randomly allocated to either a screening group, which was offered fully reimbursed DXA examinations between January and June 2023, or a control group, which received usual care, defined as DXA examination by a physician or patient on their own initiative without AI intervention. A logistic regression was used to test the difference in the primary outcome, new-onset osteoporosis, between the screening and control groups. Results Of the 40 658 enrolled participants, 4912 (12.1%) were identified by the AI model as high risk, with 2456 assigned to the screening group (mean age, 71.8 years ± 11.5 [SD]; 1909 female) and 2456 assigned to the control group (mean age, 72.1 years ± 11.8; 1872 female). A total of 315 of 2456 (12.8%) participants in the screening group underwent fully reimbursed DXA, and 237 of 315 (75.2%) were identified with new-onset osteoporosis. After including DXA results by means of usual care in both screening and control groups, the screening group exhibited higher rates of osteoporosis detection (272 of 2456 [11.1%] vs 27 of 2456 [1.1%]; odds ratio [OR], 11.2 [95% CI: 7.5, 16.7]; P < .001) compared with the control group. The ORs of osteoporosis diagnosis were increased in screening group participants who did not meet formalized criteria for DXA compared with those who did (OR, 23.2 [95% CI: 10.2, 53.1] vs OR, 8.0 [95% CI: 5.0, 12.6]; interactive P = .03). Conclusion Providing DXA screening to a high-risk group identified with AI-enabled chest radiographs can effectively diagnose more patients with osteoporosis. Clinical trial registration no. NCT05721157 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Smith and Rothenberg in this issue.

DMSO synergized with sugars: optical clearing agent modulation of optical coherence tomography of skin tissues.

The stratum corneum of the outermost skin is an important barrier impeding transdermal permeation, and permeation enhancers can reduce the barrier resistance of the stratum corneum and enhance the permeation of drugs in tissues. The optical imaging depth, signal intensity, and scattering coefficient variation rules of skin tissues in time dimension are obtained by using optical coherence tomography (OCT). The effect of optical clearing agents (OCAs) on OCT imaging is obtained by quantitatively analyzing the changes in the optical properties of tissues. D-fructose, one of the monosaccharides, and sucrose, one of the disaccharides, were selected for the ex vivo optical clearing experiments on pig skin tissues utilizing the dimethyl sulfoxide (DMSO) carrier effect. We find that DMSO synergized with sugars applied to skin tissue has a more significant increase in the optical imaging depth and signal intensity, and a reduction in the scattering coefficient with an increasing concentration of DMSO. DMSO with a high concentration and D-fructose with saturated concentration (10:1; v/v) effectively reduce light attenuation in OCT imaging and improve the image quality. This operation will also shorten the application time to minimize skin damage from hyperosmotic agents.

Artificial Intelligence-enabled Chest X-ray Classifies Osteoporosis and Identifies Mortality Risk.

A deep learning model was developed to identify osteoporosis from chest X-ray (CXR) features with high accuracy in internal and external validation. It has significant prognostic implications, identifying individuals at higher risk of all-cause mortality. This Artificial Intelligence (AI)-enabled CXR strategy may function as an early detection screening tool for osteoporosis. The aim of this study was to develop a deep learning model (DLM) to identify osteoporosis via CXR features and investigate the performance and clinical implications. This study collected 48,353 CXRs with the corresponding T score according to Dual energy X-ray Absorptiometry (DXA) from the academic medical center. Among these, 35,633 CXRs were used to identify CXR- Osteoporosis (CXR-OP). Another 12,720 CXRs were used to validate the performance, which was evaluated by the area under the receiver operating characteristic curve (AUC). Furthermore, CXR-OP was tested to assess the long-term risks of mortality, which were evaluated by Kaplan‒Meier survival analysis and the Cox proportional hazards model. The DLM utilizing CXR achieved AUCs of 0.930 and 0.892 during internal and external validation, respectively. The group that underwent DXA with CXR-OP had a higher risk of all-cause mortality (hazard ratio [HR] 2.59, 95% CI: 1.83-3.67), and those classified as CXR-OP in the group without DXA also had higher all-cause mortality (HR: 1.67, 95% CI: 1.61-1.72) in the internal validation set. The external validation set produced similar results. Our DLM uses CXRs for early detection of osteoporosis, aiding physicians to identify those at risk. It has significant prognostic implications, improving life quality and reducing mortality. AI-enabled CXR strategy may serve as a screening tool.

Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events.

Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syndrome or conduction disorders, predicting PMI is challenging, as patients often experience related symptoms. This study was designed to create a deep learning model (DLM) for predicting future PMI from ECG data and assess its ability to predict future cardiovascular events. In this study, a DLM was trained on a dataset of 158,471 ECGs from 42,903 academic medical center patients, with additional validation involving 25,640 medical center patients and 26,538 community hospital patients. Primary analysis focused on predicting PMI within 90 days, while all-cause mortality, cardiovascular disease (CVD) mortality, and the development of various cardiovascular conditions were addressed with secondary analysis. The study's raw ECG DLM achieved area under the curve (AUC) values of 0.870, 0.878, and 0.883 for PMI prediction within 30, 60, and 90 days, respectively, along with sensitivities exceeding 82.0% and specificities over 81.9% in the internal validation. Significant ECG features included the PR interval, corrected QT interval, heart rate, QRS duration, P-wave axis, T-wave axis, and QRS complex axis. The AI-predicted PMI group had higher risks of PMI after 90 days (hazard ratio [HR]: 7.49, 95% CI: 5.40-10.39), all-cause mortality (HR: 1.91, 95% CI: 1.74-2.10), CVD mortality (HR: 3.53, 95% CI: 2.73-4.57), and new-onset adverse cardiovascular events. External validation confirmed the model's accuracy. Through ECG analyses, our AI DLM can alert clinicians and patients to the possibility of future PMI and related mortality and cardiovascular risks, aiding in timely patient intervention.

Enhancement of stimulated Raman scattering of a weak vibration mode in tetrahydrofuran through the energy-transfer resonance of lycopene.

A method of energy-transfer resonance of lycopene used to enhance stimulated Raman scattering (SRS) of a weak vibration C-O mode in tetrahydrofuran (THF) was developed in this study. Only C-H SRS was observed in pure THF at high energies. When lycopene was added, the C-O SRS located at 915 cm-1 of the weak vibration mode in THF was observed. The maximum SRS enhancement of the C-O mode was achieved when the concentration was 3.72 × 10-6 mol/L because of the resonance enhancement of the solute, which transferred the excess vibrational energy to the solvent. Moreover, the pulse width compression phenomenon of the C-H vibration in the presence of C-O SRS was obtained.

An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration.

Emergency department (ED) triage scale determines the priority of patient care and foretells the prognosis. However, the information retrieved from the initial assessment is limited, hindering the risk identification accuracy of triage. Therefore, we sought to develop a 'dynamic' triage system as secondary screening, using artificial intelligence (AI) techniques to integrate information from initial assessment data and subsequent examinations. This retrospective cohort study included 134,112 ED visits with at least one electrocardiography (ECG) and chest X-ray (CXR) in a medical center from 2012 to 2022. Additionally, an independent community hospital provided 45,614 ED visits as an external validation set. We trained an eXtreme gradient boosting (XGB) model using initial assessment data to predict all-cause mortality in 7 days. Two deep learning models (DLMs) using ECG and CXR were trained to stratify mortality risks. The dynamic triage levels were based on output from the XGB-triage and DLMs from ECG and CXR. During the internal and external validation, the area under the receiver operating characteristic curve (AUC) of the XGB-triage model was >0.866; furthermore, the AUCs of DLMs using ECG and CXR were >0.862 and >0.886, respectively. The dynamic triage scale provided a higher C-index (0.914-0.920 vs. 0.827-0.843) than the original one and demonstrated better predictive ability for 5-year mortality, 30-day ED revisit, and 30-day discharge. The AI-based risk scale provides a more accurate and dynamic stratification of mortality risk in ED patients, particularly in identifying patients who tend to be overlooked due to atypical symptoms.

A Deep-Learning Algorithm-Enhanced Electrocardiogram Interpretation for Detecting Pulmonary Embolism.

Background: The early diagnosis of pulmonary embolism (PE) remains a challenge. Electrocardiograms (ECGs) and D-dimer levels are used to screen potential cases. Objective: To develop a deep learning model (DLM) to detect PE using ECGs and investigate the clinical value of false detections in patients without PE. Methods: Among patients who visited the emergency department between 2011 and 2019, PE cases were identified through a review of medical records. Non-PE ECGs were collected from patients without a diagnostic code for PE. There were 113 PE and 51,456 non-PE ECGs in the training and validation sets for developing the DLM, respectively, and 27 PE and 13,105 non-PE cases in an independent testing set for performance validation. A human-machine competition was conducted from the testing set to compare the performance of the DLM with that of physicians. Receiver operating characteristic (ROC) curves, sensitivity, and specificity were used to determine the diagnostic value. Survival analysis was used to assess the prognosis of the patients without PE, stratified by DLM prediction. Results: The DLM was as effective as physicians in diagnosing PE, with 70.8% sensitivity and 69.7% specificity. The area under the ROC curve of DLM was 0.778 in the testing set and up to 0.9 with D-dimer and demographic data. The non-PE patients whose ECG was misclassified as PE by DLM had higher all-cause mortality [hazard ratio (HR) 2.13 (1.51-3.02)] and risk of non-cardiovascular hospitalization [HR 1.55 (1.42-1.68)] than those correctly classified. Conclusions: A DLM-enhanced ECG system may prompt PE recognition and provide prognostic outcomes in patients with false-positive predictions.

Investigated hydrogen-bond network kinetics of acetone-water solutions by spontaneous and stimulated Raman spectroscopy.

The hydrogen bond (HB) network structure and kinetics of the acetone-water mixed solutions were investigated by the spontaneous Raman and stimulated Raman scattering (SRS) spectra. The HB network of water molecules was enhanced when the volume fraction of acetone ranged from 0 to 0.25. Two new SRS peaks of water at 3272 and 3380 cm-1 were obtained, resulting from the cooperation of the polar carbonyl (C = O)-enhanced HB and the ice-like structure formed around the methyl groups. However, when the volume fraction went beyond 0.25, the spontaneous Raman main peak at 3445 cm-1 showed a significant blue-shift, and the corresponding SRS signal disappeared, indicating that the HB of water was weakened, which originated from the self-association of acetone. In the meantime, the fully tetrahedral HB structure among water molecules was destroyed at the higher volume fraction (≥ 0.8). Hopefully, our study here would advance the study of HB network structures and kinetics in other aqueous solutions.

Coherent Raman comb generation in H2O2aqueous solutions by crossing-pump stimulated Raman scattering.

The cascaded stimulated Raman scattering (SRS) of 30% H2O2 aqueous solutions was investigated using a pulsed Nd: YAG laser with a wavelength of 532 nm. The transfer of excess electrons between H2O2 and H2O molecules enhanced the SRS. Together, the decomposition of H2O2 and the intense SRS Stokes led to the generation of the crossing-pump effect of H2O2 aqueous solutions and the appearance of a new peak at 4229 cm-1 that is excited by Stokes as the pump source. Crossing-pump not only reduced the threshold but also generated the broadband-coherent Raman comb, defined as a coherent radiation wavelength ranging from 434 to 831 nm (i.e., a Raman shift ranging from -4225 to 6756 cm-1). The anti-Stokes SRS was attributed to the four-wave mixing (FWM) process.

Generation of dual-supercontinuum coherent radiation in acetone mixed with carbon disulfide by stimulated Raman scattering.

Stimulated Raman scattering (SRS) in a liquid has been a major focus of nonlinear optics. Traditional SRS generates single or cascaded Stokes components arising from spontaneous Raman noise. Herein, we report the formation mechanism of a specific spectrum-continuous spectroscopy technique based on SRS of mixed liquids. SRS of a mixed acetone and carbon disulfide solution is investigated by a pulsed Nd:YAG laser with a wavelength of 532 nm. Two remarkably asymmetric broadened SRS lines are obtained. When the volume ratio is 7:3, the broadened spectral bands are optimized. The supercontinuum spectroscopy phenomenon is explained by hydrogen bond formation, adjacent vibrational modes coupling, and laser-induced plasma generation. This technique has the potential to contribute to the development of a supercontinuum Raman laser.

Periodontitis, Helicobacter pylori infection, and gastrointestinal tract cancer mortality.

AIM: Periodontitis has been proposed to lead to Helicobacter pylori infection, which could cause many gastrointestinal tract cancers. This study aimed to determine the association or otherwise between periodontitis and survival outcomes in individuals with respect to H. pylori infection. MATERIALS AND METHODS: The study population comprised 4955 subjects aged 20-90 who had received both periodontal examination and H. pylori serum test in the Third National Health and Nutrition Examination Survey (NHANES III) database. Logistic regression models were used to analyse the association between periodontitis and H. pylori seropositivity (H. pylori infection). Survival analysis was performed using the NHANES III linked to mortality data. Cox proportional hazard regression was carried out to investigate the association between periodontitis and gastrointestinal tract cancer mortality in individuals with/without H. pylori infection. RESULTS: Compared to periodontal health, periodontitis was significantly associated with increased odds of H. pylori infection (OR = 1.271, 95% CI = 1.177-1.372). Periodontitis significantly increased the mortality risk from all causes (HR = 1.574, 95% CI = 1.327-1.866) and all cancers (HR = 1.948, 95% CI = 1.701-2.232), including gastrointestinal (GI) tract cancer (HR = 4.140, 95% CI = 3.656-4.687), gastric cancer (HR = 4.288, 95% CI = 3.969-4.632), and colorectal cancer (HR = 4.814, 95% CI = 3.849-6.020) in subjects with H. pylori infection after adjusting for health-related factors. Periodontitis was significantly related to the decreased survival time in subjects with GI tract (p = .001) or colorectal cancer (p = .002) and H. pylori infection. CONCLUSION: Our study demonstrated that periodontitis was significantly associated with higher mortality risk of GI tract, gastric, and colorectal cancer in subjects with H. pylori infection. Owing to an interactive effect between periodontitis and H. pylori infection on cancer mortality, H. pylori infection has a significant moderating effect in regulating the association between periodontitis and mortality due to all cancers, including GI tract cancer and colorectal cancer.

Investigated coherent anti-Stokes Raman scattering in the process of cascaded stimulated Raman scattering in liquid and ice-Ih D2O.

Stimulated Raman scattering (SRS) of liquid and ice-Ih D2O was investigated using a pulsed Nd:YAG laser with a wavelength of 532 nm. The high-order Stokes peaks and corresponding anti-Stokes SRS [Coherent Anti-Stokes Raman Spectroscopy (CARS)] peaks were obtained. Two symmetric and antisymmetric Raman modes of stretching vibrations were observed in liquid D2O, while only a symmetric stretching vibration mode was observed in ice-Ih D2O. Pure Stokes SRS is always collinear with the pump beam along the axial direction. Some ring-like Stokes SRS and CARS shifts, which originate from four-wave mixing processes, can also be observed only in the forward direction along with different angles meeting the phase-matching criteria, respectively. Simultaneously, the temporal behavior of SRS in liquid and ice-Ih D2O was examined, and the temporal waveforms of the pump laser pulse, transmitted pump pulse, and the forward SRS pulse were measured. In both cases, SRS was the dominant contributor to stimulated scattering. However, the efficiency values drastically decreased due to the self-termination behavior of SRS in liquid D2O, which arose from the thermal self-defocusing of both the pump beam and the SRS beam, owing to the Stokes shift-related opto-heating effect. In contrast, for the SRS process in ice-Ih D2O, the thermal self-defocusing influence was negligible, benefitting from a much greater thermal conductivity and a higher conversion efficiency of SRS generation retained under both of the conditions.

Short-pulse broadband stimulated Raman scattering in carbon disulfide via resonance cascading.

Cascaded stimulated Raman scattering (SRS) of carbon disulfide (CS2) was investigated by a pulsed Nd:YAG laser with a wavelength of 532 nm. The fourth-order Stokes and second-order anti-Stokes lines were generated when the pump laser energy was about 1.909 mJ in one sample cell (C1) only. However, the same result was obtained in the second sample cell (C2) with a pump energy of 0.883 mJ. At the same time, the fifth-order Stokes line was produced in C2 when the pump energy increased to 1.208 mJ, and the coherent radiation wavelength ranged from 498 to 644 nm. The result was attributed to the resonance enhancement effect, where the frequency difference between the pump laser and the Stokes light emitted from the working medium (CS2) self-matched with the vibrational energy level of C=S, which resulted in the generation of the cascaded broadband SRS. The anti-Stokes SRS was attributed to four-wave mixing. Simultaneously, the pulse durations of the Stokes and anti-Stokes were compressed to about 380 ps by SRS and laser-induced breakdown. The resonance effect not only reduced the threshold, but it also generated broadband and short-pulse SRS.

Patient perceptions of students in a longitudinal integrated clerkship in Taiwan: a qualitative study.

BACKGROUND: Longitudinal integrated clerkships (LICs) are a model of clinical education growing rapidly in Western contexts. LICs use educational continuity to benefits students' clinical learning and professional identity formation. Patient-centered care is a core component of medical professionalism in the West. To support patient-centered care, education leaders in Taiwan restructured clinical education and implemented the first longitudinal integrated clerkship in East Asia. We aimed to investigate patients' perceptions of longitudinal relationships with the LIC students within Taiwan's Confucian cultural and social context. METHODS: We invited patients or their family members who were cared for longitudinally by a LIC student to participate in the study. Participating patients or their family members undertook semi-structured interviews. We analyzed data qualitatively using a general inductive approach to identify themes in the patients' descriptions of their experiences interacting with the LIC students. RESULTS: Twenty-five patients and family members participated in interviews: 16 patients and 9 family members. Qualitative analysis of interview transcripts identified three themes from patients' experience receiving care from their LIC students: care facilitation, companionship, and empathy. To provide care facilitation, LIC students served as a bridge between the physicians and patients. Students served patients by reminding, consulting, tracking disease progression, and researching solutions for problems. To provide companionship, students accompanied patients interpersonally like a friend or confidant who listens and provides a presence for patients. To provide empathy, patients reported that students showed sincere concern for patients' experience, feelings, and mood. CONCLUSION: In our study, Taiwanese patients' perspectives of LIC students suggested the value of care facilitation, companionship, and empathy. We discuss these themes within the context of Confucian culture and the Taiwanese context of care.

Enhanced stimulated Raman scattering of water by KOH.

Stimulated Raman scattering (SRS) of water and a 1 M KOH-H2O solution are investigated using a Nd:YAG laser in both forward and backward directions. An obvious enhanced SRS signal is realized by dissolving KOH in liquid water. Compared with pure water, the performance improvements include the appearance of low-wavenumber Raman peaks, higher Raman intensity, an increased Raman gain, and an enhanced hydrogen bonding network. In this paper, the SRS enhancement phenomenon is explained from both the hydrogen bonding structure and the mechanism of stimulated Raman scattering. We consider it to be a very important SRS enhancement technique, which is low cost, simple, but reliable. Meanwhile, it can easily be extended to other alkali hydroxides.

Excited state geometry of ß-carotene influenced by environments: the nature and decisive role of solvent revealing by two-dimensional resonance Raman correlation spectroscopy.

Resonance Raman scattering can be used to investigate the ground and excited state information of carotenoid. It is known that the Dushinsky rotation can significantly influence the resonant Raman intensity of ß-carotene (ß-car). The excited state geometry revealed by the double components feature of the C = C stretching vibrational modes and the environmental dependence of the Raman intensity for each component remain unknown. We explore the influence of environmental factors on the relative intensity of these two C = C stretching vibration modes and perform two-dimensional resonance Raman correlation analysis to reveal the changes on ß-car excited state geometry. The results show that the relative wavelength difference between the 0-0 absorption and the excitation is the key factor that decides the intensity ratio of the two components and that the intensity of each mode is modulated by environmental factors. This modulation is closely related to the excited state geometry and dynamics, effective conjugation length, and electron-phonon coupling constant. It also shows that the asynchronous cross-peaks in the two-dimensional resonance Raman correlation spectrum (2DRRCOS) can effectively characterize the degree of the varied electron-phonon coupling with the changing conditions. These results are not only complementary to the research on the excited states of carotenoids but also applicable to investigate the environmental dependence of Raman intensity for a lot of π-conjugated molecules.

Attenuated vagally-mediated heart rate variability at rest and in response to postural maneuvers in patients with generalized anxiety disorder.

BACKGROUND: Altered heart rate variability (HRV), an index of autonomic nervous system function, has been reported in generalized anxiety disorder (GAD), but the results have been mixed. Thus, the present study, using a large sample size and better methodology, aims to examine whether GAD is associated with impaired HRV, both at rest and in response to posture challenges. METHODS: In total, 1832 participants were recruited in this study, consisting of 682 patients with GAD (including 326 drug- and comorbidity-free GAD patients) and 1150 healthy controls. Short-term HRV was measured during the supine-standing-supine test (5-min per position). Propensity score matching (PSM), a relatively novel method, was used to control for potential confounders. RESULTS: After PSM algorithm, drug- and comorbidity-free GAD patients had reductions in resting (baseline) high-frequency power (HF), an index for parasympathetic modulation, and increases in the low-frequency/HF ratio (LF/HF), an index for sympathovagal balance as compared to matched controls. Furthermore, the responses of HF and LF/HF to posture changes were all attenuated when compared with matched controls. Effect sizes, given by Cohen's d, for resting HF and HF reactivity were 0.42 and 0.36-0.42, respectively. CONCLUSIONS: GAD is associated with altered sympathovagal balance, characterized by attenuation in both resting vagal modulation and vagal reactivity, with an almost medium effect size (Cohen's d ≈ 0.4), regardless of medication use or comorbidity status.