Contributions of individual qSOFA elements to assessment of severity and for prediction of mortality.

BACKGROUND: The quick sequential [sepsis-related] organ failure assessment (qSOFA) acts as a prompt to consider possible sepsis. The contributions of individual qSOFA elements to assessment of severity and for prediction of mortality remain unknown. METHODS: A total of 3974 patients with community-acquired pneumonia were recruited to an observational prospective cohort study. The area under the receiver operating characteristic curve (AUROC), odds ratio, relative risk and Youden's index were employed to assess discrimination. RESULTS: Respiratory rate ≥22/min demonstrated the most superior diagnostic value, indicated by largest odds ratio, relative risk and AUROC, and maximum Youden's index for mortality. However, the indices for altered mentation and systolic blood pressure (SBP) ≤100 mm Hg decreased notably in turn. The predictive validities of respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg were good, adequate and poor for mortality, indicated by AUROC (0.837, 0.734 and 0.671, respectively). Respiratory rate ≥22/min showed the strongest associations with SOFA scores, pneumonia severity index, hospital length of stay and costs. However, SBP ≤100 mm Hg was most weakly correlated with the indices. CONCLUSIONS: Respiratory rate ≥22/min made the greatest contribution to parsimonious qSOFA to assess severity and predict mortality. However, the contributions of altered mentation and SBP ≤100 mm Hg decreased strikingly in turn. It is the first known prospective evidence of the contributions of individual qSOFA elements to assessment of severity and for prediction of mortality, which might have implications for more accurate clinical triage decisions.

Respiratory rate ≥22/min demonstrated the most superior diagnostic value.Respiratory rate ≥22/min showed the strongest association with severity.Respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg predicted mortality well, adequately and poorly, respectively.

Identification of the nitrate pollution in surface water of Dongshan Bay based on stable isotope technology.

Identifying and quantifying water nitrate pollution is crucial for managing aquatic environment of a bay. Dongshan Bay, a significant semi-enclosed bay in the southeastern coastal area of Fujian Province, features mangrove and coral reef ecosystems at its estuary and bay mouth, respectively. Dongshan Bay is impacted by human activities such as mariculture. We quantified and analyzed nitrate pollution status in the surface waters of Dongshan Bay by measuring physicochemical parameters, stable isotopes (δ15N-NO3-, δ18O-NO3- and δ15N-NH4+) of the surface waters, and using statistical methods including the MixSIAR isotope mixing model. The results showed that the concentrations of chlorophyll a and dissolved inorganic nitrogen in the surface waters exhibited a noticeable gradient change, decreasing from the estuary of the Zhangjiang River to the mouth of Dongshan Bay. The maximum concentrations of chlorophyll a, NH4+, NO3- and NO2- were 45.2 µg·L-1, 52.67 µmol·L-1, 379.2 µmol·L-1 and 3.93 µmol·L-1, respectively. The nitrogen and oxygen isotope values of NH4+ and NO3- in the surface waters showed significant spatial variations. According to the MixSIAR model results, nitrogen sources in the surface waters of Dongshan Bay were mainly freshwater inputs of the Zhangjiang River estuary, aquaculture wastewater, and groundwater. The freshwater input from the Zhangjiang River estuary contributed the most (25.2%), while aquaculture wastewater, groundwater and urban sewage accounted for 24.6%, 19.0%, and 15.1%, respectively. It is evident that freshwater input from the Zhangjiang River estuary is the primary source of nitrate in the surface waters of Dongshan Bay.

A Novel Artificial Intelligence-Based Classification of Highly Myopic Eyes Based on Visual Function and Fundus Features.

Purpose: To develop a novel classification of highly myopic eyes using artificial intelligence (AI) and investigate its relationship with contrast sensitivity function (CSF) and fundus features. Methods: We enrolled 616 highly myopic eyes of 616 patients. CSF was measured using the quantitative CSF method. Myopic macular degeneration (MMD) was graded according to the International META-PM Classification. Thickness of the macula and peripapillary retinal nerve fiber layer (p-RNFL) were assessed by fundus photography and optical coherence tomography, respectively. Classification was performed by combining CSF and fundus features with principal component analysis and k-means clustering. Results: With 83.35% total variance explained, highly myopic eyes were classified into four AI categories. The percentages of AI categories 1 to 4 were 14.9%, 37.5%, 36.2%, and 11.4%, respectively. Contrast acuity of the eyes in AI category 1 was the highest, which decreased by half in AI category 2. For AI categories 2 to 4, every increase in category led to a decrease of 0.23 logarithm of the minimum angle of resolution in contrast acuity. Compared with those in AI category 1, eyes in AI category 2 presented a higher percentage of MMD2 and thinner temporal p-RNFL. Eyes in AI categories 3 and 4 presented significantly higher percentage of MMD ≥ 3, thinner nasal macular thickness and p-RNFL (P < 0.05). Multivariate regression showed AI category 4 had higher MMD grades and thinner macular compared with AI category 3. Conclusions: We proposed an AI-based classification of highly myopic eyes with clear relevance to visual function and fundus features. Translational Relevance: This classification helps to discover the early hidden visual deficits of highly myopic patients, becoming a useful tool to evaluate the disease comprehensively.

Application of preset coronary artery orifice patch in Bentall surgery.

BACKGROUND: Bentall surgery is the main method for treating aortic root lesions, but traditional Bentall method is very difficult for patients with mild aortic sinus dilation to directly anastomose the coronary artery orifice with graft. CASE PRESENTATION: A 41-year-old man was admitted to hospital after severe chest pain. Computed tomography angiography(CTA)revealed a type A aortic dissection. Echocardiography showed moderate aortic valve regurgitation and an aortic sinus diameter of 38 mm( mm). The patient underwent emergency Bentall surgery (using a preset coronary artery orifice patch), total arch replacement, and implantation of a graft into the descending aorta. Follow-up echocardiography showed the patient cardiac function was good, and there was no residual leakage at the coronary artery orifice. CONCLUSIONS: This method is an alternative to traditional Bentall surgery and is suitable for all aortic root lesions, especially those with mild aortic sinus dilation or concomitant aortic dissection.

Relationship between serum iron, zinc, calcium, and HIF-1a-comparative analysis of 2 regions and 4 ethnic groups in China.

Background: Altitude illness has serious effects on individuals who are not adequately acclimatized to high-altitude areas and may even lead to death. However, the individualized mechanisms of onset and preventive measures are not fully elucidated at present, especially the relationship between altitude illness and elements, which requires further in-depth research. Methods: Fresh serum samples were collected from individuals who underwent health examinations at the two hospitals in Xining and Sanya between November 2021 and December 2021. The blood zinc (Zn), iron (Fe), and calcium (Ca) concentrations, as well as hypoxia-inducible factor 1-alpha (HIF-1α) concentrations, were measured. This study conducted effective sample size estimation, repeated experiments, and used GraphPad Prism 9.0 and IBM SPSS version 19.0 software for comparative analysis of differences in the expression of elements and HIF-1α among different ethnic groups, altitudes, and concentration groups. Linear regression and multiple linear regression were employed to explore the relationships among elements and their correlation with HIF-1α. Results: This study included a total of 400 participants. The results from the repeated measurements indicated that the consistency of the laboratory test results was satisfactory. In terms of altitude differences, except for Fe (p = 0.767), which did not show significant variance between low and high altitude regions, Zn, Ca, and HIF-1α elements all exhibited notable differences between these areas (p < 0.0001, p = 0.004, and p < 0.0001). When grouping by the concentrations of elements and HIF-1α, the results revealed significant variations in the distribution of zinc among different levels of iron and HIF-1α (p < 0.05). The outcomes of the linear regression analysis demonstrated that calcium and zinc, iron and HIF-1α, calcium and HIF-1α, and zinc and HIF-1α displayed substantial overall explanatory power across different subgroups (p < 0.05). Finally, the results of the multiple linear regression analysis indicated that within the high-altitude population, the Li ethnic group in Sanya, and the Han ethnic group in Sanya, the multiple linear regression model with HIF-1αas the dependent variable and elements as the independent variables exhibited noteworthy overall explanatory power (p < 0.05). Conclusion: The levels of typical elements and HIF-1α in the blood differ among various altitudes and ethnic groups, and these distinctions may be linked to the occurrence and progression of high-altitude illness.

qPRF: A system to accelerate population receptive field decoding.

Patterns of BOLD response can be decoded using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). The time cost of evaluating the PRF model is high, often requiring days to decode BOLD signals for a small cohort of subjects. We introduce the qPRF, an efficient method for decoding that reduced the computation time by a factor of 1436 when compared to another widely available PRF decoder (Kay, Winawer, Mezer and Wandell, 2013) on a benchmark of data from the Human Connectome Project (HCP; Van Essen, Smith, Barch, Behrens, Yacoub and Ugurbil, 2013). With a specially designed data structure and an efficient search algorithm, the qPRF optimizes the five PRF model parameters according to a least-squares criterion. To verify the accuracy of the qPRF solutions, we compared them to those provided by Benson, Jamison, Arcaro, Vu, Glasser, Coalson, Van Essen, Yacoub, Ugurbil, Winawer and Kay (2018). Both hemispheres of the 181 subjects in the HCP data set (a total of 10,753,572 vertices, each with a unique BOLD time series of 1800 frames) were decoded by qPRF in 15.2 hours on an ordinary CPU. The absolute difference in R 2 reported by Benson et al. and achieved by the qPRF was negligible, with a median of 0.39% ( R 2 units being between 0% and 100%). In general, the qPRF yielded a slightly better fitting solution, achieving a greater R 2 on 99.7% of vertices. The qPRF may facilitate the development and computation of more elaborate models based on the PRF framework, as well as the exploration of novel clinical applications.

Presaccadic Attention Enhances and Reshapes the Contrast Sensitivity Function Differentially around the Visual Field.

Contrast sensitivity (CS), which constrains human vision, decreases from fovea to periphery, from the horizontal to the vertical meridian, and from the lower vertical to the upper vertical meridian. It also depends on spatial frequency (SF), and the contrast sensitivity function (CSF) depicts this relation. To compensate for these visual constraints, we constantly make saccades and foveate on relevant objects in the scene. Already before saccade onset, presaccadic attention shifts to the saccade target and enhances perception. However, it is unknown whether and how it modulates the interplay between CS and SF, and if this effect varies around polar angle meridians. CS enhancement may result from a horizontal or vertical shift of the CSF, increase in bandwidth, or any combination. In addition, presaccadic attention could enhance CS similarly around the visual field, or it could benefit perception more at locations with poorer performance (i.e., vertical meridian). Here, we investigated these possibilities by extracting key attributes of the CSF of human observers. The results reveal that presaccadic attention (1) increases CS across SF, (2) increases the most preferred and the highest discernable SF, and (3) narrows the bandwidth. Therefore, presaccadic attention helps bridge the gap between presaccadic and postsaccadic input by increasing visibility at the saccade target. Counterintuitively, this CS enhancement was more pronounced where perception is better-along the horizontal than the vertical meridian-exacerbating polar angle asymmetries. Our results call for an investigation of the differential neural modulations underlying presaccadic perceptual changes for different saccade directions.

Hierarchical Bayesian Augmented Hebbian Reweighting Model of Perceptual Learning.

The Augmented Hebbian Reweighting Model (AHRM) has been effectively utilized to model the collective performance of observers in various perceptual learning studies. In this work, we have introduced a novel hierarchical Bayesian Augmented Hebbian Reweighting Model (HB-AHRM) to simultaneously model the learning curves of individual participants and the entire population within a single framework. We have compared its performance to that of a Bayesian Inference Procedure (BIP), which independently estimates the posterior distributions of model parameters for each individual subject without employing a hierarchical structure. To cope with the substantial computational demands, we developed an approach to approximate the likelihood function in the AHRM with feature engineering and linear regression, increasing the speed of the estimation procedure by 20,000 times. The HB-AHRM has enabled us to compute the joint posterior distribution of hyperparameters and parameters at the population, observer, and test levels, facilitating statistical inferences across these levels. While we have developed this methodology within the context of a single experiment, the HB-AHRM and the associated modeling techniques can be readily applied to analyze data from various perceptual learning experiments and provide predictions of human performance at both the population and individual levels. The likelihood approximation concept introduced in this study may have broader utility in fitting other stochastic models lacking analytic forms.

Coarse-Grained Modeling of Liquid-Liquid Phase Separation in Cells: Challenges and Opportunities.

Liquid-liquid phase separation (LLPS) within cells gives rise to membraneless organelles, which play pivotal roles in numerous cellular functions. A comprehensive understanding of the functional aspects of intrinsically disordered protein (IDP) condensates necessitates elucidating their inherent structures and establishing correlations with biological functions. Coarse-grained (CG) molecular dynamics (MD) simulations present a promising avenue for gaining insights into LLPS mechanisms of biomacromolecules. Essential to this endeavor is the development of tailored CG force fields for MD simulations, incorporating the full spectrum of biomolecules involved in the formation of condensates and accounting for real-time biochemical reactions coupled to the LLPS. Moreover, developing accurate theoretical frameworks and establishing links between condensate structure and its function are imperative for a thorough comprehension of LLPS of biological systems.

Erythrocyte membrane biomimetic EGCG nanoparticles attenuate renal injury induced by diquat through the NF-κB/NLRP3 inflammasome pathway.

Diquat (DQ) poisoning can cause multiple organ damage, and the kidney is considered to be the main target organ. Increasing evidence shows that alleviating oxidative stress and inflammatory response has promising application prospects. Epigallocatechin gallate (EGCG) has potent antioxidant and anti-inflammatory effects. In this study, red blood cell membrane (RBCm)-camouflaged polylactic-co-glycolic acid (PLGA) nanoparticles (NPs) were synthesized to deliver EGCG (EGCG-RBCm/NPs) for renal injury induced by DQ. Human renal tubular epithelial cells (HK-2 cells) were stimulated with 600 µM DQ for 12 h and mice were intraperitoneally injected with 50 mg/kg b.w. DQ, followed by 20 mg/kg b.w./day EGCG or EGCG-RBCM/NPs for 3 days. The assessment of cellular vitality was carried out using the CCK-8 assay, while the quantification of reactive oxygen species (ROS) was performed through ROS specific probes. Apoptosis analysis was conducted by both flow cytometry and TUNEL staining methods. Pathological changes in renal tissue were observed. The expressions of NLRP3, IL-1ß, IL-18, NFκB and Caspase1 were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR), immunohistochemistry, immunofluorescence, and Western blot. The results showed that the DQ group had increased ROS expression, increased the level of oxidative stress, and increased apoptosis rate compared with the control group. Histopathological analysis of mice in the DQ group showed renal tubular injury and elevated levels of blood urea nitrogen (BUN), serum creatinine (SCr), kidney injury molecule-1 (KIM-1), and cystatin C (Cys C). Furthermore, the DQ group exhibited heightened expression of NLRP3, p-NFκB p65, Caspase1 p20, IL-1ß, and IL-18. However, EGCG-RBCm/NPs treatment mitigated DQ-induced increases in ROS, apoptosis, and oxidative stress, as well as renal toxicity and decreases in renal biomarker levels. Meanwhile, the expression of the above proteins were significantly decreased, and the survival rate of mice was ultimately improved, with an effect better than that of the EGCG treatment group. In conclusion, EGCG-RBCm/NPs can improve oxidative stress, inflammation, and apoptosis induced by DQ. This effect is related to the NF-κB/NLRP3 inflammasome pathway. Overall, this study provides a new approach for treating renal injury induced by DQ.

How the window of visibility varies around polar angle.

Contrast sensitivity, the amount of contrast required to detect or discriminate an object, depends on spatial frequency (SF): The Contrast Sensitivity Function (CSF) peaks at intermediate SFs and drops at lower and higher SFs and is the basis of computational models of visual object recognition. The CSF varies from foveal to peripheral vision, but only a couple studies have assessed changes around polar angle of the visual field. Sensitivity is generally better along the horizontal than the vertical meridian, and better at the lower vertical than the upper vertical meridian, yielding polar angle asymmetries. Here, we investigate CSF attributes at polar angle locations at both group and individual levels, using Hierarchical Bayesian Modeling. This method enables precise estimation of CSF parameters by decomposing the variability of the dataset into multiple levels and analyzing covariance across observers. At the group level, peak contrast sensitivity and corresponding spatial frequency with the highest sensitivity are higher at the horizontal than vertical meridian, and at the lower than upper vertical meridian. At an individual level, CSF attributes (e.g., maximum sensitivity, the most preferred SF) across locations are highly correlated, indicating that although the CSFs differ across locations, the CSF at one location is predictive of the CSF at another location. Within each location, the CSF attributes co-vary, indicating that CSFs across individuals vary in a consistent manner (e.g., as maximum sensitivity increases, so does the SF at which sensitivity peaks), but more so at the horizontal than the vertical meridian locations. These results show similarities and uncover some critical polar angle differences across locations and individuals, suggesting that the CSF should not be generalized across iso-eccentric locations around the visual field. Our window of visibility varies with polar angle: It is enhanced and more consistent at the horizontal meridian.

Chitosan oligosaccharides alleviate macrophage pyroptosis and protect sepsis mice via activating the Nrf2/GPX4 pathway.

In the process of sepsis, excessive occurrence of pyroptosis, a form of programmed cell death acting as a defense mechanism against pathogens, can disrupt immune responses, thus leading to tissue damage and organ dysfunction. Chitosan oligosaccharide (COS), derived from chitosan degradation, has demonstrated diverse beneficial effects. However, its impact on sepsis-induced pyroptosis remains unexplored. In the present study, ATP/LPS was utilized to induce canonical-pyroptosis in THP-1 cells, while bacterial outer membrane vesicles (OMV) were employed to trigger non-canonical pyroptosis in RAW264.7 cells. Our results revealed a dose-dependent effect of COS on both types of pyroptosis. This was evidenced by a reduction in the expression of pro-inflammatory cytokines, as well as crucial regulatory proteins involved in pyroptosis. In addition, COS inhibited the cleavage of caspase-1 and GSDMD, and reduced ASC oligomerization. The underlying mechanism revealed that COS acts an antioxidant, reducing the release of pyroptosis-induced ROS and malondialdehyde (MDA) by upregulation the expression and promoting the nuclear translocation of nuclear factor erythroid-2-related factor 2 (Nrf2), which led to an elevation of glutathione peroxidase 4 (GPX4) and superoxide dismutase (SOD). Notably, the actions of COS were completely reversed by the Nrf2 inhibitor. Consequently, COS intervention increased the survival rate of sepsis.

Identification of microbial communities and multi-species biofilms contamination in seafood processing environments with different hygiene conditions.

Biofilms formed by spoilage and pathogenic bacteria increase microbial persistence, causing an adverse influence on the quality of seafood. The mono-species biofilms are widely reported, however, the contamination of multi-species biofilms and their matrix in food environments are still not fully understood. Here, we assessed the contamination of multi-species biofilms in three seafood processing environments with different hygiene levels by detecting bacterial number and three biofilm matrix components (carbohydrates, extracellular DNA (eDNA), and proteins). Samples comprising seven food matrix surfaces and eight food processing equipment surfaces were collected from two seafood processing plants (XY and XC) and one seafood market (CC). The results showed that the bacterial counts ranged from 1.89 to 4.91 CFU/cm2 and 5.68 to 9.15 BCE/cm2 in these surfaces by cultivation and real-time PCR, respectively. Six biofilm hotspots were identified, including four in CC and two in XY. Among the three processing environments, the amplicon sequence variants (ASVs) of Proteobacteria, Bacteroidetes, and Actinobacteria decreased with improved processing hygiene, while Firmicutes showed a decrease in the four most abundant phyla. The most prevalent bacteria belonged to genera Psychrobacter, Acinetobacter, and Pseudomonas, demonstrating the significant differences and alteration in bacterial community composition during different environments. From the biofilm hotspots, 15 isolates with strong biofilm forming ability were identified, including 7 Pseudomonas, 7 Acinetobacter, and 1 Psychrobacter. The Pseudomonas isolates exhibited the highest production of EPS components and three strong motilities, whose characteristics were positively correlated. Thus, this study verified the presence of multi-species biofilms in seafood processing environments, offering preliminary insights into the diversity of microbial communities during processing. It highlights potential contamination sources and emphasizes the importance of understanding biofilms composition to control biofilms formation in seafood processing environments.

A mitochondria-specific NIR fluorescence probe for dual-detection of sulfur dioxide and viscosity in living cells and mice.

The level of sulfur dioxide (SO2) and viscosity in mitochondria play vital roles in various physiological and pathological processes. Abnormalities in mitochondrial SO2 and viscosity are closely associated with numerous biological diseases. It is of great significance to develop novel fluorescence probes for simultaneous detection of SO2 and viscosity within mitochondria. Herein, we have developed a water-soluble, mitochondrial-targeted and near-infrared fluorescent probe, CMBT, for the simultaneous detection of SO2 and viscosity. The probe CMBT incorporates benzothiazolium salt as a mitochondrial targeting moiety and 7-diethylaminocoumarin as a rotor for viscosity detection, respectively. Based on the prompt reaction between nucleophilic HSO3-/SO32- and the backbone of the benzothiazolium salt derivative, probe CMBT displayed high sensitivity and selectivity toward SO2 with a limit of detection as low as 0.17 µM. As viscosity increased, the twisted intramolecular charge transfer (TICT) process was restricted, resulting in fluorescence emission enhancement at 690 nm. Moreover, probe CMBT demonstrated exceptional mitochondrial targeting ability and was successfully employed to image variations of SO2 and viscosity in living cells and mice. The work highlights the great potential of the probe as a convenient tool for revealing the relationship between SO2 and viscosity in biological systems.

Transfer of visual perceptual learning over a task-irrelevant feature through feature-invariant representations: Behavioral experiments and model simulations.

A large body of literature has examined specificity and transfer of perceptual learning, suggesting a complex picture. Here, we distinguish between transfer over variations in a "task-relevant" feature (e.g., transfer of a learned orientation task to a different reference orientation) and transfer over a "task-irrelevant" feature (e.g., transfer of a learned orientation task to a different retinal location or different spatial frequency), and we focus on the mechanism for the latter. Experimentally, we assessed whether learning a judgment of one feature (such as orientation) using one value of an irrelevant feature (e.g., spatial frequency) transfers to another value of the irrelevant feature. Experiment 1 examined whether learning in eight-alternative orientation identification with one or multiple spatial frequencies transfers to stimuli at five different spatial frequencies. Experiment 2 paralleled Experiment 1, examining whether learning in eight-alternative spatial-frequency identification at one or multiple orientations transfers to stimuli with five different orientations. Training the orientation task with a single spatial frequency transferred widely to all other spatial frequencies, with a tendency to specificity when training with the highest spatial frequency. Training the spatial frequency task fully transferred across all orientations. Computationally, we extended the identification integrated reweighting theory (I-IRT) to account for the transfer data (Dosher, Liu, & Lu, 2023; Liu, Dosher, & Lu, 2023). Just as location-invariant representations in the original IRT explain transfer over retinal locations, incorporating feature-invariant representations effectively accounted for the observed transfer. Taken together, we suggest that feature-invariant representations can account for transfer of learning over a "task-irrelevant" feature.

Improving iconic memory through contrast detection training with HOA-corrected vision.

Iconic memory and short-term memory are not only crucial for perception and cognition, but also of great importance to mental health. Here, we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning. Normal adults were trained in a contrast detection task for ten days, with their higher-order aberrations (HOA) corrected in real-time. We found that the training improved not only their contrast sensitivity function (CSF), but also their iconic memory and baseline information maintenance for short-term memory, and the relationship between memory and CSF improvements could be well-predicted by an observer model. These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition. They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.

Visual Function and Driving Performance Under Different Lighting Conditions in Older Drivers: Preliminary Results From an Observational Study.

BACKGROUND: Age-related vision changes significantly contribute to fatal crashes at night among older drivers. However, the effects of lighting conditions on age-related vision changes and associated driving performance remain unclear. OBJECTIVE: This pilot study examined the associations between visual function and driving performance assessed by a high-fidelity driving simulator among drivers 60 and older across 3 lighting conditions: daytime (photopic), nighttime (mesopic), and nighttime with glare. METHODS: Active drivers aged 60 years or older participated in visual function assessments and simulated driving on a high-fidelity driving simulator. Visual acuity (VA), contrast sensitivity function (CSF), and visual field map (VFM) were measured using quantitative VA, quantitative CSF, and quantitative VFM procedures under photopic and mesopic conditions. VA and CSF were also obtained in the presence of glare in the mesopic condition. Two summary metrics, the area under the log CSF (AULCSF) and volume under the surface of VFM (VUSVFM), quantified CSF and VFM. Driving performance measures (average speed, SD of speed [SDspeed], SD of lane position (SDLP), and reaction time) were assessed under daytime, nighttime, and nighttime with glare conditions. Pearson correlations determined the associations between visual function and driving performance across the 3 lighting conditions. RESULTS: Of the 20 drivers included, the average age was 70.3 years; 55% were male. Poor photopic VA was significantly correlated with greater SDspeed (r=0.26; P<.001) and greater SDLP (r=0.31; P<.001). Poor photopic AULCSF was correlated with greater SDLP (r=-0.22; P=.01). Poor mesopic VUSFVM was significantly correlated with slower average speed (r=-0.24; P=.007), larger SDspeed (r=-0.19; P=.04), greater SDLP (r=-0.22; P=.007), and longer reaction times (r=-0.22; P=.04) while driving at night. For functional vision in the mesopic condition with glare, poor VA was significantly correlated with longer reaction times (r=0.21; P=.046) while driving at night with glare; poor AULCSF was significantly correlated with slower speed (r=-0.32; P<.001), greater SDLP (r=-0.26; P=.001) and longer reaction times (r=-0.2; P=.04) while driving at night with glare. No other significant correlations were observed between visual function and driving performance under the same lighting conditions. CONCLUSIONS: Visual functions differentially affect driving performance in different lighting conditions among older drivers, with more substantial impacts on driving during nighttime, especially in glare. Additional research with larger sample sizes is needed to confirm these results.

Novel Quantitative Contrast Sensitivity Function Enhances the Prediction of Treatment Outcome and Recurrence in Amblyopia.

Purpose: Although effective amblyopia treatments are available, treatment outcome is unpredictable, and the condition recurs in up to 25% of the patients. We aimed to evaluate whether a large-scale quantitative contrast sensitivity function (CSF) data source, coupled with machine learning (ML) algorithms, can predict amblyopia treatment response and recurrence in individuals. Methods: Visual function measures from traditional chart vision acuity (VA) and novel CSF assessments were used as the main predictive variables in the models. Information from 58 potential predictors was extracted to predict treatment response and recurrence. Six ML methods were applied to construct models. The SHapley Additive exPlanations was used to explain the predictions. Results: A total of 2559 consecutive records of 643 patients with amblyopia were eligible for modeling. Combining variables from VA and CSF assessments gave the highest accuracy for treatment response prediction, with the area under the receiver operating characteristic curve (AUC) of 0.863 and 0.815 for outcome predictions after 3 and 6 months, respectively. Variables from the VA assessment alone predicted the treatment response, with AUC values of 0.723 and 0.675 after 3 and 6 months, respectively. Variables from the CSF assessment gave rise to an AUC of 0.909 for recurrence prediction compared to 0.539 for VA assessment alone, and adding VA variables did not improve predictive performance. The interocular differences in CSF features are significant contributors to recurrence risk. Conclusions: Our models showed CSF data could enhance treatment response prediction and accurately predict amblyopia recurrence, which has the potential to guide amblyopia management by enabling patient-tailored decision making.

Enabling identification of component processes in perceptual learning with nonparametric hierarchical Bayesian modeling.

Perceptual learning is a multifaceted process, encompassing general learning, between-session forgetting or consolidation, and within-session fast relearning and deterioration. The learning curve constructed from threshold estimates in blocks or sessions, based on tens or hundreds of trials, may obscure component processes; high temporal resolution is necessary. We developed two nonparametric inference procedures: a Bayesian inference procedure (BIP) to estimate the posterior distribution of contrast threshold in each learning block for each learner independently and a hierarchical Bayesian model (HBM) that computes the joint posterior distribution of contrast threshold across all learning blocks at the population, subject, and test levels via the covariance of contrast thresholds across blocks. We applied the procedures to the data from two studies that investigated the interaction between feedback and training accuracy in Gabor orientation identification over 1920 trials across six sessions and estimated learning curve with block sizes L = 10, 20, 40, 80, 160, and 320 trials. The HBM generated significantly better fits to the data, smaller standard deviations, and more precise estimates, compared to the BIP across all block sizes. In addition, the HBM generated unbiased estimates, whereas the BIP only generated unbiased estimates with large block sizes but exhibited increased bias with small block sizes. With L = 10, 20, and 40, we were able to consistently identify general learning, between-session forgetting, and rapid relearning and adaptation within sessions. The nonparametric HBM provides a general framework for fine-grained assessment of the learning curve and enables identification of component processes in perceptual learning.