Multiplexed bulk and single-cell RNA-seq hybrid enables cost-efficient disease modeling with chimeric organoids.

Disease modeling with isogenic Induced Pluripotent Stem Cell (iPSC)-differentiated organoids serves as a powerful technique for studying disease mechanisms. Multiplexed coculture is crucial to mitigate batch effects when studying the genetic effects of disease-causing variants in differentiated iPSCs or organoids, and demultiplexing at the single-cell level can be conveniently achieved by assessing natural genetic barcodes. Here, to enable cost-efficient time-series experimental designs via multiplexed bulk and single-cell RNA-seq of hybrids, we introduce a computational method in our Vireo Suite, Vireo-bulk, to effectively deconvolve pooled bulk RNA-seq data by genotype reference, and thereby quantify donor abundance over the course of differentiation and identify differentially expressed genes among donors. Furthermore, with multiplexed scRNA-seq and bulk RNA-seq, we demonstrate the usefulness and necessity of a pooled design to reveal donor iPSC line heterogeneity during macrophage cell differentiation and to model rare WT1 mutation-driven kidney disease with chimeric organoids. Our work provides an experimental and analytic pipeline for dissecting disease mechanisms with chimeric organoids.

Real-world evidence from a retrospective study on suicide during depression: clinical characteristics, treatment patterns and disease burden.

BACKGROUND: Suicide stands as both a primary symptom and the direst outcome of major depressive disorder (MDD). The scarcity of effective treatment strategies makes managing MDD patients with suicide especially challenging. Hence, it is crucial to investigate disease characteristics and efficacious therapeutic strategies for these patients, drawing insights from disease databases and real-world data. METHODS: In this retrospective study, MDD patients hospitalized between January 2013 and December 2020 were investigated using Electronic Health Records (EHR) data from Beijing Anding Hospital. The study enrolled 4138 MDD patients with suicidal ideation or behavior (MDS) and 3848 without (MDNS). Demographic data, clinical attributes, treatment approaches, disease burden, and re-hospitalization within one year of discharge were extracted and compared. RESULTS: Patients in the MDS group were predominantly younger and female, exhibiting a higher prevalence of alcohol consumption, experiencing frequent life stress events, and having an earlier onset age. Re-hospitalizations within six months post-discharge in the MDS group were significantly higher than in the MDNS group (11.36% vs. 8.91%, p < 0.001). Moreover, a more considerable fraction of MDS patients underwent combined electroconvulsive therapy treatment (56.72% vs. 43.71%, p < 0.001). Approximately 38% of patients in both groups were prescribed two or more therapeutic regimes, and over 90% used antidepressants, either alone or combined. Selective serotonin reuptake inhibitors (SSRIs) were the predominant choice in both groups. Furthermore, antidepressants were often prescribed with antipsychotics or mood stabilizers. When medication alterations were necessary, the favoured options involved combination with antipsychotics or transitioning to alternative antidepressants. Yet, in the MDS group, following these initial modifications, the addition of mood stabilizers tended to be the more prioritized alternative. CONCLUSIONS: MDD patients with suicidal ideation or behaviour displayed distinctive demographic and clinical features. They exhibited intricate treatment patterns, a pronounced burden of illness, and an increased likelihood of relapse.

Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine.

Forest fires threaten global ecosystems, socio-economic structures, and public safety. Accurately assessing forest fire susceptibility is critical for effective environmental management. Supervised learning methods dominate this assessment, relying on a substantial dataset of forest fire occurrences for model training. However, obtaining precise forest fire location data remains challenging. To address this issue, semi-supervised learning emerges as a viable solution, leveraging both a limited set of collected samples and unlabeled data containing environmental factors for training. Our study employed the transductive support vector machine (TSVM), a key semi-supervised learning method, to assess forest fire susceptibility in scenarios with limited samples. We conducted a comparative analysis, evaluating its performance against widely used supervised learning methods. The assessment area for forest fire susceptibility lies in Dayu County, Jiangxi Province, China, renowned for its vast forest cover and frequent fire incidents. We analyzed and generated maps depicting forest fire susceptibility, evaluating prediction accuracies for both supervised and semi-supervised learning methods across various small sample scenarios (e.g., 4, 8, 12, 16, 20, 24, 28, and 32 samples). Our findings indicate that TSVM exhibits superior prediction accuracy compared to supervised learning with limited samples, yielding more plausible forest fire susceptibility maps. For instance, at sample sizes of 4, 16, and 28, TSVM achieves prediction accuracies of approximately 0.8037, 0.9257, and 0.9583, respectively. In contrast, random forests, the top performers in supervised learning, demonstrate accuracies of approximately 0.7424, 0.8916, and 0.9431, respectively, for the same small sample sizes. Additionally, we discussed three key aspects: TSVM parameter configuration, the impact of unlabeled sample size, and performance within typical sample sizes. Our findings support semi-supervised learning as a promising approach compared to supervised learning for forest fire susceptibility assessment and mapping, particularly in scenarios with small sample sizes.

Assessment of Reference Genes Stability in Cortical Bone of Obese and Diabetic Mice.

Introduction: Bone, a pivotal structural organ, is susceptible to disorders with profound health implications. The investigation of gene expression in bone tissue is imperative, particularly within the context of metabolic diseases such as obesity and diabetes that augment the susceptibility to bone fractures. The objective of this study is to identify a set of internal control genes for the analysis of gene expression. Methods: This study employs reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) to assess gene expression in bone tissue. We selected fourteen housekeeping genes and assessed their stability in the cortical bone of mouse models for obesity and diabetes using four well-established algorithms (GeNorm, BestKeeper, NormFinder, and the comparative Delta Ct method). Results and Conclusion: We identified Rpl13a as the mostly stably expressed reference gene in cortical bone tissue from mouse models of obesity and diabetes (db/db), while Gapdh was found to be the most stable reference gene in another diabetes model, KKAy mice. Additionally, Ef1a, Ppia, Rplp0, and Rpl22 were identified as alternative genes suitable for normalizing gene expression in cortical bone from obesity and diabetes mouse models. These findings enhance RT-qPCR accuracy and reliability, offering a strategic guide to select reference gene for studying bone tissue gene expression in metabolic disorders.

Hybrid approach for accurate water demand prediction using socio-economic and climatic factors with ELM optimization.

This study proposes a hybrid approach for accurately predicting water demand by integrating socio-economic variables, such as population and GDP (per capita), with climatic variables, including temperature and precipitation. The prediction model utilizes an Extreme Learning Machine (ELM), effectively capturing the dynamic relationships between the input variables and water demand. The Improved Ant Nesting Algorithm is employed to fine-tune the weights and biases to optimize the network's performance. To evaluate the predictive accuracy of the model, a comprehensive dataset consisting of socio-economic and climatic factors is utilized for training and testing purposes. Performance metrics, namely Root Mean Square Error (RMSE) and Correlation Coefficients (R2), are employed as evaluation criteria. The results demonstrate that the hybrid approach achieves accurate water supply predictions, showcasing its potential to contribute significantly to effective water resource management and decision-making processes. Based on the results, IANA-ELM is considered the best model due to its high R2 values. Specifically, in the training data, the R2 values are 0.693 for population, 0.624 for GDP per capita, 0.607 for temperature, and 0.708 for rainfall. Similarly, in the test data, the R2 values are 0.672 for population, 0.608 for GDP per capita, 0.592 for temperature, and 0.708 for rainfall. This integrated approach provides a robust tool for policymakers, water utility companies, and researchers in the field of water managements, enabling them to make informed decisions based on accurate predictions of water demand.

The Synergistic Effect on the Mimetic Optical Structure of Feline Eyes toward Household Health Monitoring of Acute and Chronic Diseases.

A breakthrough in the performance of bionic optical structures will only be achieved if we can obtain an in-depth understanding of the synergy mechanisms operating in natural optical structures and find ways to imitate them. In this work, inspired by feline eyes, an optical substrate that takes advantage of a synergistic effect that occurs between resonant and reflective structures was designed. The synergistic effect between the reflective and resonant components leads to a Raman enhancement factor (EF) of 1.16 × 107, which is much greater than that achieved using the reflective/resonant cavities on their own. Finite-difference time-domain (FDTD) simulations and experimental results together confirm that the mechanism of this synergistic effect is achieved by realizing multiple reflections and repeated absorptions of light, generating a strong local electric field. Thus, a 2-3 order of magnitude increase in sensitivity could be achieved. More importantly, with the homemade centrifugal device, above optical substrates were further used to develop a rapidly highly sensitive household health monitoring system (detection time <3 min). It can thus be used to give early warning of acute diseases with high risk (e.g., acute myocardial infarction (AMI) and cerebral peduncle). Due to the good reusability and storability (9% and 8% reduction in EF after washing 30 times and 9 months of storage, respectively) of the substrates, the substrates thus reduce detection costs (to ∼$1), making them much cheaper to use than the current gold-standard methods (e.g., ∼$16 for gout detection).

SEIR-diffusion modeling and stability analysis of supply chain finance based on blockchain technology.

Inadequate information sharing and difficult information diffusion are the main factors that cause upstream and downstream enterprises to default on supply chain finance. Blockchain technology, which exploits distributed storage and a consensus mechanism, can provide effective solutions to overcome these problems such as information sharing. When blockchain technology is adopted by the enterprises that comprise the supply chain finance business, this technology shows a diffusion trend. As a result, the decision pertaining to the application of novel technologies is affected. Therefore, to investigate the diffusion mechanism pertaining to the blockchain technology that is applied in supply chain finance, the study exploited the idea of a class of SEIR infectious disease models, and built a blockchain model that considers the supply chain financial system. Besides, the study verifies the stability of the model by constructing a Lyapunov function. The results indicate that the basic reproduction number determines the proliferation of the blockchain technology. When the basic reproduction number is less than 1, the proliferation of the blockchain technology that is applied in supply chain finance system would terminate. By contrast, when the basic reproduction number is greater than 1, during the average infection period, the number of non-adopting enterprises that accept the blockchain technology becomes greater than 1, which can maintain a continuous impact on supply chain finance system. Over time, the number of enterprises that accept blockchain technology tends to be stable. Through numerical simulations that consider the influencing parameters pertaining to the basic regeneration number, which has important effect on blockchain technology diffusion, we enlarge the diffusion efficiency and increase the transfer rate of potential on-chain enterprises or decrease the default exit rate. As a result, we facilitate the diffusion of blockchain technology in the system.

Efficacy and pharmacoeconomic advantages of Fufang Huangbai Fluid hydropathic compress in diabetic foot infections: a comparative clinical study with antimicrobial calcium alginate wound dressing.

Objective: To compare the intervention effects and pharmacoeconomic advantages of Fufang Huangbai Fluid (FFHB) hydropathic compress versus Antimicrobial Calcium Alginate Wound Dressing (ACAWD) in the treatment of diabetic foot infections (DFI). Methods: Patients with DF who were hospitalized in the peripheral vascular Department of Dongzhimen Hospital of Beijing University of Chinese Medicine from December 2020 to February 2022 and met the inclusion and excluding criteria were allocated into the experimental group and control group through minimization randomization. The experimental group was treated with FFHB hydropathic compress for 2 weeks, while the control group was treated with ACAWD for the same duration. The wound healing of both groups was monitored for 1 month post-discharge. Clinical data from all eligible patients were collected, and differences in various indices between cohorts were analyzed. Results: 22 in the experimental group (including two fell off) and 20 in the control group. After the treatment, the negative rate of wound culture in the experimental group was 30% and that in the control group was 10%, There was no significant difference in the negative rate of wound culture and change trend of minimum inhibitory concentration (MIC) value of drug sensitivity (p > 0.05). The infection control rate of the experimental group was 60%, and that of the control group was 25%. The difference between the two groups was statistically significant (χ2 = 5.013, p = 0.025). The median wound healing rate of the experimental group was 34.4% and that of the control group was 33.3%. There was no significant difference between the two groups (p > 0.05). During the follow-up 1 month later, the wound healing rate in the experimental group was higher, and the difference was statistically significant (p = 0.047). Pharmacoeconomic evaluations indicated that the experimental group had greater cost-effectiveness compared to the control group. Conclusion: In the preliminary study, FFHB demonstrated comparable pathogenic and clinical efficacy to ACAWD in the treatment of mild DF infection, and exhibited superior pharmacoeconomic advantages. With the aid of infection control, the wound healing rate in the FFHB group showed notable improvement. Nevertheless, due to the limited sample size, larger-scale studies are warranted to further validate these findings. Clinical Trial Registration: (https://www.chictr.org.cn/showproj.aspx?proj=66175), identifier (ChiCTR2000041443).

Comparison of diagnosis-related groups (DRG)-based hospital payment system design and implementation strategies in different countries: The case of ischemic stroke.

Diagnosis-related groups (DRG) based hospital payment systems are gradually becoming the main mechanism for reimbursement of acute inpatient care. We reviewed the existing literature to ascertain the global use of DRG-based hospital payment systems, compared the similarities and differences of original DRG versions in ten countries, and used ischemic stroke as an example to ascertain the design and implementation strategies for various DRG systems. The current challenges with and direction for the development of DRG-based hospital payment systems are also analyzed. We found that the DRG systems vary greatly in countries in terms of their purpose, grouping, coding, and payment mechanisms although based on the same classification concept and that they have tended to develop differently in countries with different income classifications. In high-income countries, DRG-based hospital payment systems have gradually begun to weaken as a mainstream payment method, while in middle-income countries DRG-based hospital payment systems have attracted increasing attention and increased use. The example of ischemic stroke provides suggestions for mutual promotion of DRG-based hospital payment systems and disease management. How to determine the level of DRG payment incentives and improve system flexibility, balance payment goals and disease management goals, and integrate development with other payment methods are areas for future research on DRG-based hospital payment systems.

Perceived Safety Assessment of Interactive Motions in Human-Soft Robot Interaction.

Soft robots, especially soft robotic hands, possess prominent potential for applications in close proximity and direct contact interaction with humans due to their softness and compliant nature. The safety perception of users during interactions with soft robots plays a crucial role in influencing trust, adaptability, and overall interaction outcomes in human-robot interaction (HRI). Although soft robots have been claimed to be safe for over a decade, research addressing the perceived safety of soft robots still needs to be undertaken. The current safety guidelines for rigid robots in HRI are unsuitable for soft robots. In this paper, we highlight the distinctive safety issues associated with soft robots and propose a framework for evaluating the perceived safety in human-soft robot interaction (HSRI). User experiments were conducted, employing a combination of quantitative and qualitative methods, to assess the perceived safety of 15 interactive motions executed by a soft humanoid robotic hand. We analyzed the characteristics of safe interactive motions, the primary factors influencing user safety assessments, and the impact of motion semantic clarity, user technical acceptance, and risk tolerance level on safety perception. Based on the analyzed characteristics, we summarize vital insights to provide valuable guidelines for designing safe, interactive motions in HSRI. The current results may pave the way for developing future soft machines that can safely interact with humans and their surroundings.

The impact of price and image warnings on the social perception of gifting cigarettes in China.

INTRODUCTION: The tobacco gift-giving culture in China poses a significant challenge to public health; however, there is limited research on effectively curbing the tobacco gift-giving culture and its associated tobacco gift consumption. This study examines the potential impact of two tobacco control measures that the Chinese government may consider adopting on cigarette gifting behavior in the future in Chinese society. METHODS: This study employed a randomized survey experiment to examine the effects of cigarette price treatment and pictorial health warning labels (HWLs) on cigarette gifting. The total sample size of this study is 1035. Four groups of participants were presented with representative cigarettes categorized into high-, medium-, and low-priced products, along with different prices (normal and double) or external packaging imagery (normal and pictorial HWL versions). RESULTS: The price of cigarettes for personal consumption forms an L-shaped distribution, and the price of cigarette gifts forms a W-shaped distribution. Increasing cigarette prices reduces smokers' willingness to gift high-priced cigarettes but stimulates the consumption of low-price cigarettes as gifts. Pictorial HWLs do not directly influence smokers' intentions to gift cigarettes, but they enhance the effectiveness of price regulation concerning medium-priced cigarette products. CONCLUSIONS: If the price variance of cigarettes is not reduced, the effect of price regulation will be very limited. Implementing combined interventions of pictorial HWLs and price regulation or modifying the pricing structure of tobacco products may yield stronger control outcomes.

Assessment of relationships between bullous pemphigoid and neurological diseases: A bidirectional two-sample Mendelian randomization study.

Bullous pemphigoid (BP) is the most prevalent autoimmune vesiculobullous skin illness that tends to affect the elderly. Growing evidence has hinted a correlation between BP and neurological diseases. However, existing observational studies contained inconsistent results, and the causality and direction of their relationship remain poorly understood. To assess the causal relationship between BP and neurological disorders, including Alzheimer's disease (AD), multiple sclerosis (MS), Parkinson's disease (PD), and stroke. A bidirectional two-sample Mendelian randomization (MR) adopted independent top genetic variants as instruments from the largest accessible genome-wide association studies (GWASs), with BP (n = 218 348), PD (n = 482 730), AD (n = 63 926), stroke (n = 446 696), and MS (n = 115 803). Inverse variance weighted (IVW), MR-Egger, weighted mode methods, weighted median, and simple mode were performed to explore the causal association. Multiple sensitivity analyses, MR-Pleiotropy Residual Sum and Outlier (PRESSO) was used to evaluate horizontal pleiotropy and remove outliers. With close-to-zero effect estimates, no causal impact of BP on the risk of the four neurological diseases was discovered. However, we found that MS was positively correlated with higher odds of BP (OR = 1.220, 95% CI: 1.058-1.408, p = 0.006), while no causal associations were observed between PD (OR = 0.821, 95% CI: 0.616-1.093, p = 0.176), AD (OR = 1.066, 95% CI: 0.873-1.358, p = 0.603), stroke (OR = 0.911, 95% CI: 0.485-1.713, p = 0.773) and odds of BP. In summary, no causal impact of BP on the risk of PD, AD, MS and stroke was detected in our MR analysis. However, reverse MR analysis identified that only MS was positively correlated with higher odds of BP, but not PD, AD and stroke.

Cost-Effectiveness of Pharmacist Care in Diabetes Management: A Systematic Review.

INTRODUCTION: In recent years, the role of pharmacists has undergone significant transformation to become more patient-centered and involved in managing chronic diseases. Nonetheless, it remains unclear whether pharmacist involvement in diabetes management is cost-effective. This study aimed to systematically review the cost-effectiveness and reporting quality in comprehensive economic evaluations of pharmacist management compared to standard care in diabetes. METHODS: Eligible studies included cost-effectiveness analyses employing pharmacist professional services as the intervention for diabetes. A literature search was conducted in the bibliographic databases Pubmed, Scopus, China National Knowledge Infrastructure (CNKI), and the International Health Technology Assessment (HTA) database from their inception until July 2023. Two independent reviewers performed title, abstract, full-text screening, and data abstraction and assessed the quality of reporting and methodological approaches using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) checklists. RESULTS: Twelve studies were identified with an average research quality score of 19.8, including cost-utility (n = 5) and cost-effectiveness (n = 7) analyses, with only four studies rated as high quality. The efficacy data were derived from randomized controlled trials (n = 7), retrospective studies (n = 2), and published literature sources (n = 2). Half of the included studies were conducted in high-income countries, while the other half was in upper-middle and lower-middle-income countries, respectively. Despite significant variations in the cost of pharmacist intervention, consistent findings demonstrate that pharmacist involvement in diabetes management is more cost-effective or even cost-saving than standard care, primarily attributed to better glycemic control, enhanced patient compliance, and reduced risks of medication-related problems. CONCLUSION: This systematic review substantiates that pharmacist involvement in diabetes management is cost-effective compared with standard care. However, the overall quality of reporting needs to be improved, and high-quality evidence is urgently needed to support healthcare decision-making in pharmacy practice.

A biosensor for D-2-hydroxyglutarate in frozen sections and intraoperative assessment of IDH mutation status.

The oncometabolite D-2-hydroxyglutarate (D-2-HG) has emerged as a valuable biomarker in tumors with isocitrate dehydrogenase (IDH) mutations. Efficient detection methods are required and rapid intraoperative determination of D-2-HG remains a huge challenge. Herein, D-2-HG dehydrogenase from Achromobacter xylosoxidans (AX-D2HGDH) was found to have high substrate specificity. AX-D2HGDH dehydrogenizes D-2-HG and reduces flavin adenine dinucleotide (FAD) bound to the enzyme. Interestingly, the dye resazurin can be taken as another substrate to restore FAD. AX-D2HGDH thus catalyzes a bisubstrate and biproduct reaction: the dehydrogenation of D-2-HG to 2-ketoglutarate and simultaneous reduction of non-fluorescent resazurin to highly fluorescent resorufin. According to steady-state analysis, a ping-pong bi-bi mechanism has been concluded. The Km values for resazurin and D-2-HG were determined as 0.56 µM and 10.93 µM, respectively, suggesting high affinity to both substrates. On the basis, taking AX-D2HGDH and resazurin as recognition and fluorescence transducing element, a D-2-HG biosensor (HGAXR) has been constructed. HGAXR exhibits high sensitivity, accuracy and specificity for D-2-HG in different biological samples. With the aid of HGAXR and the matched low-cost palm-size detecting device, D-2-HG levels in frozen sections of resected brain tumor tissues can be measured in a direct, simple and accurate manner with a fast detection (1-3 min). As the technique of frozen section is familiar to surgeons and pathologists, HGAXR and the portable device can be easily integrated into the current workflow, having potential to provide rapid intraoperative pathology for IDH mutation status and guide decision-making during surgery.

Peripheral neutrophils and oxidative stress-associated molecules for predicting the severity of asthma: a cross-sectional study based on multidimensional assessment.

Objectives: This study aims to explore the relationship between the severity of asthma and neutrophils and related oxidative stress-associated molecules in peripheral blood and induced sputum. Methods: A total of 67 subjects were included in this study, namely, 25 patients with severe asthma and 42 patients with non-severe asthma. Clinical data, induced sputum and peripheral blood were collected. Lung function and molecules related to oxidative stress in induced sputum and peripheral blood of asthma patients were detected. The relationship between neutrophils and asthma severity was analyzed. HDAC2 mRNA and protein expression levels and HDAC2 activity were also analyzed. Multivariate logistic regression was performed to select statistically significant variables. Results: The absolute value of neutrophils and percentage of neutrophils were higher in the severe asthma patients. These two values were used to predict the severity of asthma by ROC analysis, with the best cutoff values being 4.55 × 109/L (sensitivity 83.3%, specificity 64.0%) and 55.15% (sensitivity 54.8%, specificity 88.0%). The ROS concentration of neutrophils in the induced sputum samples and the 8-iso-PGF2α concentration in the peripheral blood samples were higher in the severe asthma group (P = 0.012; P = 0.044), whereas there was reduced HDAC2 protein activity in PBMCs (P < 0.001). A logistic equation and a nomogram were created to give a precise prediction of disease severity. Conclusion: Oxidative stress is increased in severe asthma patients. Peripheral blood neutrophils and 8-iso-PGF2α can be used as biomarkers to predict the severity of asthma. A prediction model was created for evaluating asthma severity.

Selection and prediction of metro station sites based on spatial data and random forest: a study of Lanzhou, China.

Urban economic development, congestion relief, and traffic efficiency are all greatly impacted by the thoughtful planning of urban metro station layout. with the urban area of Lanzhou as an example, the suitability of the station locations of the built metro stations of the rail transit lines 1 and 2 in the study area have been evaluated using multi-source heterogeneous spatial data through data collection, feature matrix construction, the use of random forest and K-fold cross-validation, among other methods. The average Gini reduction value was used to examine the contribution rate of each feature indicator based on the examination of model truthfulness. According to the study's findings: (1) K-fold cross-validation was applied to test the random forest model that was built using the built metro stations and particular factors. The average accuracy of the tests and out-of-bag data (OOB) of tenfold cross-validation were 89.62% and 91.285%, respectively. Additionally, the AUC area under the ROC curve was 0.9823, indicating that this time, from the perspective of the natural environment, traffic location, and social factors The 19 elements selected from the views of the urban function structure, social economics, and natural environment are closely associated to the locations of the metro station in the research region, and the prediction the findings are more reliable; (2) It becomes apparent that more than half of the built station sites display excellent agreement with the predicted sites in terms of geographical location by superimposing the built metro station sites with the prediction results and tally up their cumulative prediction probability values within the 300 m buffering zone; (3) Based on the contribution rate of each indicator to the model, transport facilities, companies, population density, night lighting, science, education and culture, residential communities, and road network density are identified as the primary influential factors, each accounting for over 6.6%. Subsequently, land use, elevation, and slope are found to have relatively lower contributions. The results of the research provided important information for the local metro's best location selection and planning.

Assessment of visual function in blind mice and monkeys with subretinally implanted nanowire arrays as artificial photoreceptors.

Retinal prostheses could restore image-forming vision in conditions of photoreceptor degeneration. However, contrast sensitivity and visual acuity are often insufficient. Here we report the performance, in mice and monkeys with induced photoreceptor degeneration, of subretinally implanted gold-nanoparticle-coated titania nanowire arrays providing a spatial resolution of 77.5 µm and a temporal resolution of 3.92 Hz in ex vivo retinas (as determined by patch-clamp recording of retinal ganglion cells). In blind mice, the arrays allowed for the detection of drifting gratings and flashing objects at light-intensity thresholds of 15.70-18.09 µW mm-2, and offered visual acuities of 0.3-0.4 cycles per degree, as determined by recordings of visually evoked potentials and optomotor-response tests. In monkeys, the arrays were stable for 54 weeks, allowed for the detection of a 10-µW mm-2 beam of light (0.5° in beam angle) in visually guided saccade experiments, and induced plastic changes in the primary visual cortex, as indicated by long-term in vivo calcium imaging. Nanomaterials as artificial photoreceptors may ameliorate visual deficits in patients with photoreceptor degeneration.

Psychometric Properties of the Chinese Version of the ElectroConvulsive Therapy Cognitive Assessment: An Electroconvulsive Therapy-Specific Cognitive Screening Tool.

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective somatic treatment, but it may be limited by cognitive adverse effects. The existing cognitive screening instruments often lack specificity to ECT-associated cognitive deficits. The ElectroConvulsive Therapy Cognitive Assessment was developed and validated in a clinical setting, but the reliability and validity of the Chinese version of ElectroConvulsive Therapy Cognitive Assessment (ECCA-C) have not been studied in a large clinical sample. METHODS: The ECCA-C and the Montreal Cognitive Assessment (MoCA) were administered to patients with major depressive disorder (MDD) undergoing ECT at 3 time points: pretreatment (baseline), before the fifth treatment, and 1 week posttreatment. The instruments were also administered to a sample of healthy subjects. RESULTS: Sixty-five patients with MDD and 50 age- and sex-matched healthy controls were recruited in this study. Overall, the patient group had statistically significantly lower MoCA and ECCA-C scores than the control group (both P values <0.001). The Cronbach α of the ECCA-C was 0.88 at baseline. Statistically significant decreases over time were observed in ECCA-C: pre-ECT (23.9 ± 4.0) > mid-ECT (21.3 ± 3.4) > post-ECT (18.7 ± 4.8) (all P values <0.001), whereas no statistically significant changes in MoCA scores were found at these 3 time points (F = 1.86, P = 0.165). A cutoff score of 26.5 on the ECCA-C was found to best differentiate between MDD patients and healthy controls. CONCLUSIONS: The ECCA-C showed satisfactory psychometric properties and may be a more sensitive instrument than the MoCA to assess cognitive impairment associated with ECT.

Environmental cadmium exposure alters the internal microbiota and metabolome of Sprague-Dawley rats.

Cadmium (Cd) is a toxic element that can negatively affect both humans and animals. It enters the human and animal bodies through the respiratory and digestive tracts, following which it tends to accumulate in different organs, thereby seriously affecting human and animal health, as well as hampering social and economic development. Cd exposure can alter the composition of intestinal microbiota. In addition, it can damage the peripheral organs by causing the translocation of intestinal microbiota. However, the relationship between translocation-induced changes in the composition of microbiome in the blood and metabolic changes remains unclear. In the present study, we investigated the effects of Cd exposure on microbiota and serum metabolism in rats by omics analysis. The results demonstrated that Cd exposure disrupted the balance between the blood and intestinal flora in Sprague-Dawley (SD) rats, with a significant increase in gut microbiota (Clostridia_UCG_014, NK4A214_group) and blood microbiome (Corynebacterium, Muribaculaceae). However, Cd exposure caused the translocation of Corynebacterium and Muribaculaceae from the gut into the blood. In addition, Cd exposure was associated with the up-regulation of serum indoxyl sulfate, phenyl sulfate, and p-cresol sulfate; down-regulation of δ-tocopherol and L-glutamine; and changes in blood microbiome and metabolites. In conclusion, we identified novel metabolic biomarkers for Cd toxicity, which will also expand our understanding of the role of blood microbiome in Cd-induced injury.