A high-density 1,024-channel probe for brain-wide recordings in non-human primates.

Large-scale neural population recordings with single-cell resolution across the primate brain remain challenging. Here we introduce the Neuroscroll probe that isolates single neuronal activities simultaneously from 1,024 densely spaced channels that are flexibly distributed across the shank of the probe. The Neuroscroll probe length is easily tunable for individual probes from 10 mm to 90 mm, covering the brain size of non-human primates and humans, and the probes remain intact and functional after repeated bending deformations. The Neuroscroll probes provided reliable recordings from large neural populations with high chronic stability up to 105 weeks in rats. Recording with each Neuroscroll probe yielded hundreds of well-isolated single units simultaneously from multiple brain regions distributed across the entire depth of the rhesus macaque brain. With the thousand simultaneously recorded channels, unprecedented probe length, excellent mechanical stability and flexible recording site distribution, the Neuroscroll probes enable a wide range of new experimental paradigms in system neuroscience studies with great versatility.

IRAK-M Plays A Role in the Pathology of Amyotrophic Lateral Sclerosis Through Suppressing the Activation of Microglia.

Microglial activation plays a crucial role in the disease progression in amyotrophic lateral sclerosis (ALS). Interleukin receptor-associated kinases-M (IRAK-M) is an important negative regulatory factor in the Toll-like receptor 4 (TLR4) pathway during microglia activation, and its mechanism in this process is still unclear. In the present study, we aimed to investigate the dynamic changes of IRAK-M and its protective effects for motor neurons in SOD1-G93A mouse model of ALS. qPCR (Real-time Quantitative PCR Detecting System) were used to examine the mRNA levels of IRAK-M in the spinal cord in both SOD1-G93A mice and their age-matched wild type (WT) littermates at 60, 100 and 140 days of age. We established an adeno-associated virus 9 (AAV9)-based platform by which IRAK-M was targeted mostly to microglial cells to investigate whether this approach could provide a protection in the SOD1-G93A mouse. Compared with age-matched WT mice, IRAK-M mRNA level was elevated at 100 and 140 days in the anterior horn region of spinal cords in the SOD1-G93A mouse. AAV9-IRAK-M treated SOD1-G93A mice showed reduction of IL-1ß mRNA levels and significant improvements in the numbers of spinal motor neurons in spinal cord. Mice also showed previously reduction of muscle atrophy. Our data revealed the dynamic changes of IRAK-M during ALS pathological progression and demonstrated that an AAV9-IRAK-M delivery was an effective and translatable therapeutic approach for ALS. These findings may help identify potential molecular targets for ALS therapy.

Shape-changing electrode array for minimally invasive large-scale intracranial brain activity mapping.

Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

Automated machine learning for early prediction of acute kidney injury in acute pancreatitis.

BACKGROUND: Acute kidney injury (AKI) represents a frequent and grave complication associated with acute pancreatitis (AP), substantially elevating both mortality rates and the financial burden of hospitalization. The aim of our study is to construct a predictive model utilizing automated machine learning (AutoML) algorithms for the early prediction of AKI in patients with AP. METHODS: We retrospectively analyzed patients who were diagnosed with AP in our hospital from January 2017 to December 2021. These patients were randomly allocated into a training set and a validation set at a ratio of 7:3. To develop predictive models for each set, we employed the least absolute shrinkage and selection operator (LASSO) algorithm along with AutoML. A nomogram was developed based on multivariate logistic regression analysis outcomes. The model's efficacy was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Additionally, the performance of the model constructed via AutoML was evaluated using decision curve analysis (DCA), feature importance, SHapley Additive exPlanations (SHAP) plots, and locally interpretable model-agnostic explanations (LIME). RESULTS: This study incorporated a total of 437 patients who met the inclusion criteria. Out of these, 313 were assigned to the training cohort and 124 to the validation cohort. In the training and validation cohorts, AKI occurred in 68 (21.7%) and 29(23.4%) patients, respectively. Comparative analysis revealed that the AutoML models exhibited enhanced performance over traditional logistic regression (LR). Furthermore, the deep learning (DL) model demonstrated superior predictive accuracy, evidenced by an area under the ROC curve of 0.963 in the training set and 0.830 in the validation set, surpassing other comparative models. The key variables identified as significant in the DL model within the training dataset included creatinine (Cr), urea (Urea), international normalized ratio (INR), etiology, smoking, alanine aminotransferase (ALT), hypertension, prothrombin time (PT), lactate dehydrogenase (LDH), and diabetes. CONCLUSION: The AutoML model, utilizing DL algorithm, offers considerable clinical significance in the early detection of AKI among patients with AP.

Metal-polyphenol "prison" attenuated bacterial outer membrane vesicle for chemodynamics promoted in situ tumor vaccines.

As natural adjuvants, the bacterial outer membrane vesicles (OMV) hold great potential in cancer vaccines. However, the inherent immunotoxicity of OMV and the rarity of tumor-specific antigens seriously hamper the clinical translation of OMV-based cancer vaccines. Herein, metal-phenolic networks (MPNs) are used to attenuate the toxicity of OMV, meanwhile, provide tumor antigens via the chemodynamic effect induced immunogenic cell death (ICD). Specifically, MPNs are assembled on the OMV surface through the coordination reaction between ferric ions and tannic acid. The iron-based "prison" is locally collapsed in the tumor microenvironment (TME) with both low pH and high ATP features, and thus the systemic toxicity of OMV is significantly attenuated. The released ferric ions in TME promote the ICD of cancer cells through Fenton reaction and then the generation of abundant tumor antigens, which can be used to fabricate in-situ vaccines by converging with OMV. Together with the immunomodulatory effect of OMV, potent tumor repression on a bilateral tumor model is achieved with good biosafety.

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined with serological indicators for early prediction of severe acute pancreatitis (SAP) by automated ML (AutoML). PATIENTS AND METHODS: The clinical data, of the patients with acute pancreatitis (AP) hospitalized in Hospital 1 and hospital 2 from January 2017 to December 2021, were retrospectively analyzed. Serological indicators within 24 hours of admission were collected. MCTSI score was completed by noncontrast computed tomography within 24 hours of admission. Data from the hospital 1 were adopted for training, and data from the hospital 2 were adopted for external validation. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of AP. Models were built using traditional logistic regression and AutoML analysis with 4 types of algorithms. The performance of models was evaluated by the receiver operating characteristic curve, the calibration curve, and the decision curve analysis based on logistic regression and decision curve analysis, feature importance, SHapley Additive exPlanation Plot, and Local Interpretable Model Agnostic Explanation based on AutoML. RESULTS: A total of 499 patients were used to develop the models in the training data set. An independent data set of 201 patients was used to test the models. The model developed by the Deep Neural Net (DL) outperformed other models with an area under the receiver operating characteristic curve (areas under the curve) of 0.907 in the test set. Furthermore, among these AutoML models, the DL and gradient boosting machine models achieved the highest sensitivity values, both exceeding 0.800. CONCLUSION: The AutoML model based on the MCTSI score combined with serological indicators has good predictive value for SAP in the early stage.

Catch bond-inspired hydrogels with repeatable and loading rate-sensitive specific adhesion.

Biological receptor-ligand adhesion governed by mammalian cells involves a series of mechanochemical processes that can realize reversible, loading rate-dependent specific interfacial bonding, and even exhibit a counterintuitive behavior called catch bonds that tend to have much longer lifetimes when larger pulling forces are applied. Inspired by these catch bonds, we designed a hydrogen bonding-meditated hydrogel made from acrylic acid-N-acryloyl glycinamide (AA-NAGA) copolymers and tannic acids (TA), which formed repeatable specific adhesion to polar surfaces in an ultra-fast and robust way, but hardly adhered to nonpolar materials. It demonstrated up to five-fold increase in shear adhesive strength and interfacial adhesive toughness with external loading rates varying from 5 to 500 mm min-1. With a mechanochemical coupling model based on Monte Carlo simulations, we quantitatively revealed the nonlinear dependence of rate-sensitive interfacial adhesion on external loading, which was in good agreement with the experimental data. Likewise, the developed hydrogels were biocompatible, possessed antioxidant and antibacterial properties and promoted wound healing. This work not only reports a stimuli-responsive hydrogel adhesive suitable for multiple biomedical applications, but also offers an innovative strategy for bionic designs of smart hydrogels with loading rate-sensitive specific adhesion for various emerging areas including flexible electronics and soft robotics.

In Vivo Imaging for the Visualization of Extracellular Vesicle-Based Tumor Therapy.

Extracellular vesicles (EVs) exhibiting versatile biological functions provide promising prospects as natural therapeutic agents and drug delivery vehicles. For future clinical translation, revealing the fate of EVs in vivo, especially their accumulation at lesion sites, is very important. The continuous development of in vivo imaging technology has made it possible to track the real-time distribution of EVs. This article reviews the applications of mammal-, plant-, and bacteria-derived EVs in tumor therapy, the labeling methods of EVs for in vivo imaging, the advantages and disadvantages of different imaging techniques, and possible improvements for future work.

Treatment of inflammatory bowel disease: Potential effect of NMN on intestinal barrier and gut microbiota.

Nicotinamide mononucleotide (NMN) exerts physiological effects in mammals through its conversion to nicotinamide adenine dinucleotide (NAD+). In this study, we established experimental models of colitis by mixing drinking water of C57BL/6J mice with dextran sodium sulphate (DSS), and then fed them with the same concentration of NMN or at the same time. After NMN treatment, we observed improved morphology of inflamed intestines, slightly restored length of colon, improved barrier function and reduced proinflammatory factors expression in serum. Also, significant alterations in the composition and abundance of intestinal flora in IBD mice were found. The abundance of Firmicutes, Verrucomicrobia, Akkermansia and Lactobacillus, considered as beneficial bacteria, increased, while Bacteroidetes and Muribaculaceae unclassifiably decreased. Taken together, these results suggest that NMN may improve intestinal inflammation, reduce intestinal mucosal permeability and repair gut flora dysbiosis in IBD.

Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer.

Recent studies have proposed that pyruvate dehydrogenase E1 component subunit alpha (PDHA1), a cuproptosis-key gene, is crucial to the glucose metabolism reprogram of tumor cells. However, the functional roles and regulated mechanisms of PDHA1 in multiple cancers are largely unknown. The Cancer Genome Atlas (TCGA), GEPIA2, and cBioPortal databases were utilized to elucidate the function of PDHA1 in 33 tumor types. We found that PDHA1 was aberrantly expressed in most cancer types. Lung adenocarcinoma (LUAD) patients with high PDHA1 levels were significantly correlated with poor prognosis of overall survival (OS) and first progression (FP). Kidney renal clear cell carcinoma (KIRC) patients with low PDHA1 levels displayed poor OS and disease-free survival (DFS). However, for stomach adenocarcinoma (STAD), the downregulated PDHA1 expression predicted a good prognosis in patients. Moreover, we evaluated the mutation diversity of PDHA1 in cancers and their association with prognosis. We also analyzed the protein phosphorylation and DNA methylation of PDHA1 in various tumors. The PDHA1 expression was negatively correlated with tumor-infiltrating immune cells, such as myeloid dendritic cells (DCs), B cells, and T cells in pan-cancers. Mechanically, we used single-cell sequencing to discover that the PDHA1 expression had a close link with several cancer-associated signaling pathways, such as DNA damage, cell invasion, and angiogenesis. At last, we conducted a co-expressed enrichment analysis and showed that aberrantly expressed PDHA1 participated in the regulation of mitochondrial signaling pathways, including oxidative phosphorylation, cellular respiration, and electron transfer activity. In summary, PDHA1 could be a prognostic and immune-associated biomarker in multiple cancers.

Correlations of ALD, Keap-1, and FoxO4 expression with traditional tumor markers and clinicopathological characteristics in colorectal carcinoma.

Aldolase A (A-2) (ALD), Kelch-like-ECH associated protein-1 (Keap-1), and Forkhead box O4 (FoxO4) are key regulatory proteins, which have been proven to be involved in tumor development. However, the clinicopathological significance of ALD, Keap-1, and FoxO4 expressions in colorectal (colon) carcinoma (CRC) is not clearly known. We sought to explore the clinicopathological significance of ALD, Keap-1, and FoxO4 in CRC to provide evidences for potential monitoring index of CRC. Cases of 199 CRC patients were analyzed retrospectively. Evaluation of ALD, cAMP response element-binding protein-2, cyclo-oxygenase 2, FoxO4, Keap-1, and p53 expressions in CRC patients was accomplished with immunohistochemical technique. The patients were divided into negative and positive groups in accordance with immunohistochemical result. We compared the clinicopathological characteristics of the patients in the 2 groups, coupled with analysis of the relationship between 6 aforesaid proteins and clinicopathological characteristics. Herein, we confirmed the association of tumor location with the expression of ALD, Keap-1, and FoxO4. Also, tumor differentiation was observed to associate significantly with the expression of Keap-1, FoxO4, and Cox-2. The data also revealed that there was a correlation between smoking and expression of ALD, Keap-1, FoxO4, p53, and Cox-2. Nevertheless, insignificant difference was observed when clinicopathological characteristics were compared with cAMP response element-binding protein-2 expression. These findings suggest that ALD, Keap-1, and FoxO4 reinvolved in CRC development, and thus may be considered as potential monitoring protein for CRC.

Accurate quantification, naked eyes detection and bioimaging of nitrite using a colorimetric and near-infrared fluorescent probe in food samples and Escherichia coli.

Nitrite (NO2-) is an inorganic contaminant that exists widely in the environment including water and food products, excessive amounts of NO2- would threaten humans and aquatic life. Developing a rapid and convenient sensing method for NO2- remains a great challenge. Herein, a colorimetric and near-infrared fluorescent probe (TBM) was synthesized and applied for sensitively and selectively detecting NO2- in water, food samples and Escherichia coli (E. coli). With the addition of NO2-, the probe TBM solution has a distinct visual color changed from red to colorless and fluorescence intensity at 620 nm quickly decreased. The probe TBM could detect NO2- quantitatively with a detection limit of 85 nM based on a 3σ/slope. Under optimum conditions, TBM has been successfully used to detect NO2- in real-world environmental and dietary samples, with positive results. Besides, paper strips loaded with TBM have been used to visually determine NO2- levels. Most importantly, TBM has also been proven to be able to discriminate from different concentrations of NO2- in E. coli by fluorescence imaging. In summary, the probe TBM was successfully developed for the accurate quantification, naked eyes detection and bioimaging of NO2- in water, food samples and E. coli, which provides a useful tool to better guarantee the quality and safety of daily life and food industry.

Phytochemical Engineered Bacterial Outer Membrane Vesicles for Photodynamic Effects Promoted Immunotherapy.

Cancer vaccines are emerging as an attractive modality for tumor immunotherapy. However, their practical application is seriously impeded by the complex fabrication and unsatisfactory outcomes. Herein, we construct bacterial outer membrane vesicles (OMVs)-based in situ cancer vaccine with phytochemical features for photodynamic effects-promoted immunotherapy. By simply fusing thylakoid membranes with OMVs, bacteria-plant hybrid vesicles (BPNs) are prepared. After systemic administration, BPNs can target tumor tissues and stimulate the activation of immune cells, including dendritic cells (DCs). The photodynamic effects derived from thylakoid lead to the disruption of local tumors and then the release of tumor-associated antigens that are effectively presented by DCs, inducing remarkable tumor-specific CD8+T cell responses. Moreover, BPNs can efficiently ameliorate the immunosuppressive tumor microenvironment and further boost immune responses. Therefore, both tumor development and metastasis can be efficiently prevented. This work provides a novel idea for developing a versatile membrane-based hybrid system for highly efficient tumor treatment.

Response surface model based emission source contribution and meteorological pattern analysis in ozone polluted days.

Urban and regional ozone (O3) pollution is a public health concern and causes damage to ecosystems. Due to the diverse emission sources of O3 precursors and the complex interactions of air dispersion and chemistry, identifying the contributing sources of O3 pollution requires integrated analysis to guide emission reduction plans. In this study, the meteorological characteristics leading to O3 polluted days (in which the maximum daily 8-h average O3 concentration is higher than the China Class II National O3 Standard (160 µg/m3)) in Guangzhou (GZ, China) were analyzed based on data from 2019. The O3 formation regimes and source apportionments under various prevailing wind directions were evaluated using a Response Surface Modeling (RSM) approach. The results showed that O3 polluted days in 2019 could be classified into four types of synoptic patterns (i.e., cyclone, anticyclone, trough, and high pressure approaching to sea) and were strongly correlated with high ambient temperature, low relative humidity, low wind speed, variable prevailing wind directions. Additionally, the cyclone pattern strongly promoted O3 formation due to its peripheral subsidence. The O3 formation was nitrogen oxides (NOx)-limited under the northerly wind, while volatile organic compounds (VOC)-limited under other prevailing wind directions. Anthropogenic emissions contributed largely to the O3 formation (54-78%) under the westerly, southwesterly, easterly, southeasterly, or southerly wind, but only moderately (35-47%) under the northerly or northeasterly wind. Furthermore, as for anthropogenic contributions, local emission contributions were the largest (39-60%) regardless of prevailing wind directions, especially the local NOx contributions (19-43%); the dominant upwind regional emissions contributed 12-46% (e.g., contributions from Dongguan were 12-20% under the southeasterly wind). The emission control strategies for O3 polluted days should focus on local emission sources in conjunction with the emission reduction of upwind regional sources.

Long-term treatment of Nicotinamide mononucleotide improved age-related diminished ovary reserve through enhancing the mitophagy level of granulosa cells in mice.

Ovarian aging affects the reproductive health of elderly women due to decline in oocyte quality, which is closely related to mitochondrial dysfunction. Nicotinamide mononucleotide (NMN), as a precursor of NAD+, effectively regulate mitochondria metabolism in mice. However, roles of NMN in improving age-related diminished ovary reserve remain to be determined. In present study, 4, 8, 12, 24, 40-week old female ICR mice were collected and a 20-week-long administration of NMN was conducted to 40-week-old mice (60WN), meanwhile the control group is given water (60WC). First, we found that 20-week-long administration of NMN to 40-week-old mice exhibited anti-aging and anti-inflammatory effects on organ structures, along with the improvement of estrus cycle condition and endocrine function. The number of primordial, primary, secondary, antral follicles and corpora luteum of ovaries in 60WN group was significantly increased compared with those in 60WC group. Additionally, the protein and gene expressions of P16 of ovaries were significantly reduced in 60WN group than in 60WC group. the mitochondria biogenesis, autophagy level, and proteases activity enhanced in granulosa cells after 20-week-administration of NMN. Present results indicate that NMN has the potential to save diminished ovary reserve by long-term treatment, providing a basis for exploring the role of NMN in anti-ovarian aging by enhancing the mitophagy level of granulosa cells.

Clinical characteristics and risk factors of Talaromyces marneffei infection in human immunodeficiency virus-negative patients: A retrospective observational study.

BACKGROUND: To investigate the clinical characteristics and risk factors of human immunodeficiency virus (HIV)-negative patients with Talaromyces marneffei (T. marneffei) infection. METHODS: We retrospectively collected the clinical information of HIV-negative patients with T. marneffei infection from January 1, 2010 to June 30, 2019, and analyzed the related risk factors of poor prognosis. RESULTS: Twenty-five cases aging 22 to 79 years were included. Manifestations of T. marneffei infection included fever, cough, dyspnea, chest pain or distress, lymphadenopathy, ear, nose, and throat (ENT) and/or skin lesions, bone or joint pain, edema and pain in the lower extremities, digestive symptoms, icterus, malaise, and hoarseness. Two cases had no comorbidity, while 23 cases suffered from autoimmune disease, pulmonary disease, cancer, and other chronic diseases. Sixteen cases had a medication history of glucocorticoids, chemotherapy or immunosuppressors. Pulmonary lesions included interstitial infiltration, nodules, atelectasis, cavitary lesions, pleural effusion or hydropneumothorax, bronchiectasis, pulmonary fibrosis, pulmonary edema, and consolidation. The incidence of osteolytic lesions was 20%. Eight patients received antifungal monotherapy, and 11 patients received combined antifungal agents. Fifteen patients survived and ten patients were dead. The Cox regression analysis showed that reduced eosinophil counts, higher levels of blood urea nitrogen (BUN), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactic dehydrogenase (LDH), myoglobin (Mb), procalcitonin (PCT), and galactomannan were related to poor prognosis (hazard ratio [HR]>1, P<0.05). CONCLUSIONS: Bone destruction is common in HIV-negative patients with T. marneffei infection. Defective cell-mediated immunity, active infection, multiple system, and organ damage can be the risk factors of poor prognosis.

NMN Maintains Intestinal Homeostasis by Regulating the Gut Microbiota.

The aim of this study was to determine the effects of long-term Nicotinamide mononucleotide (NMN) treatment on modulating gut microbiota diversity and composition, as well as its association with intestinal barrier function. In this study, C57BL/6J mice were fed different concentrations of NMN, and their feces were collected for detection of 16S rDNA and non-targeted metabolites to explore the effects of NMN on intestinal microbiota and metabolites. The results revealed that NMN increased the abundance of butyric acid-producing bacteria (Ruminococcae_UCG-014 and Prevotellaceae_NK3B31_group) and other probiotics (Akkermansia muciniphila), while the abundance of several harmful bacteria (Bilophila and Oscillibacter) were decreased after NMN treatment. Meanwhile, the level of bile acid-related metabolites in feces from the G1 group (0.1 mg/ml) was significantly increased compared to the control group, including cholic acid, taurodeoxycholic acid, taurocholic acid, glycocholic acid, and tauro-ß-muricholic acid. In addition, long-term NMN treatment affected the permeability of the intestinal mucosa. The number of goblet cells and mucus thickness increased, as well as expression of tight junction protein. These results demonstrate that NMN reduced intestinal mucosal permeability and exerts a protective effect on the intestinal tract. This study lays the foundation for exploring NMN's utility in clinical research.

New media platform's understanding of Chinese social workers' anti-epidemic actions: an analysis of network public opinion based on COVID-19.

Research on social public opinion of new media is currently an important interdisciplinary topic in the international academic community. Under the background of COVID-19, the major public health event of in China, this research took social workers as the research object who worked during the period of epidemic prevention and control. It referred to the international research on public opinion and selected 63 related hotly discussed articles and public comments on the WeChat public platform, the new Chinese Internet media. Moreover, the research conducted text mining on related public opinion with the 5 W communication model from public opinion evolution, text content, communication media, audiences, and public opinion influence, and used grounded theory building a development model of the generation of network public opinion. It also put forward the development needs of social work in the aspects of community resilience, social work practice, lack of public health social workers, and big data warning, etc., and pointed out that social work lacks its proper structural status in China's public health system and emergency management system.

Low dose contrast media in step-and-shoot coronary angiography with third-generation dual-source computed tomography: feasibility of using 30 mL of contrast media in patients with body surface area <1.7 m2.

BACKGROUND: Reducing contrast media volume in coronary computed tomography angiography minimizes the risk of adverse events but may compromise diagnostic image quality. We aimed to evaluate coronary computed tomography angiography's diagnostic image quality while using 30 mL of contrast media in patients with a body surface area <1.7 m2. METHODS: This prospective study included patients who underwent coronary computed tomography angiography from May 2018 to June 2019. The patients were divided into a low-dose group, who received 30 mL of contrast media, and a routine-dose group, who received contrast media based on body weight. Patient characteristics, coronary computed tomography angiography results, and quantitative and qualitative image results were assessed and compared. RESULTS: In total, 103 patients with a body surface area <1.7 m2 were 53 in the low-dose group and 50 in the routine-dose group. Sex, age, body surface area, body weight, and heart rate were similar between the groups (P>0.05). A contrast media volume of 30±0 mL was used for the low-dose group, and 41.62±4.59 mL was used for the routine-dose group. The low-dose group's computed tomography values were significantly different from those of the routine-dose group (P<0.05). The radiologists demonstrated agreement regarding diagnostic image quality and accuracy (kappa =0.91 and 0.85, respectively). CONCLUSIONS: Using 30 mL of contrast media for coronary computed tomography angiography in patients with a body surface area <1.7 m2 provided a suitable diagnostic image quality for coronary artery disease diagnosis. Although radiation doses were similar between the groups, the decreased contrast media volume was likely beneficial for the patients.

Evaluation of the Degree of Agreement of Four Methods for Diagnosing Diabetic Autonomic Neuropathy.

Background: There are many methods to diagnose diabetic autonomic neuropathy (DAN); however, often, the various methods do not provide consistent results. Even the two methods recommended by the American Diabetes Association (ADA) guidelines, Ewing's test and heart rate variability (HRV), sometimes give conflicting results. The purpose of this study was to evaluate the degree of agreement of the results of the Composite Autonomic Symptom Score 31 (COMPASS-31), skin sympathetic reaction (SSR) test, Ewing's test, and HRV in diagnosing DAN. Methods: Patients with type 2 diabetes were recruited and each received the COMPASS-31, SSR, Ewing's test, and HRV for the diagnosis of DAN. Patients were categorized as DAN(+) and DAN(-) by each of the tests. Kappa consistency tests were used to evaluate the agreement of diagnosing DAN between any two methods. Spearman's correlation test was used to evaluate the correlations of the severity of DAN between any two methods. Receiver operating characteristic (ROC) analyses were used to evaluate the diagnostic value and the cutoff value of each method. Results: A total of 126 type 2 diabetic patients were included in the study. The percentages of DAN(+) results by HRV, Ewing's test, COMPASS-31, and SSR were 61, 40, 35, and 33%, respectively. COMPASS-31 and Ewing's test had the best agreement for diagnosing DAN (κ = 0.512, p < 0.001). COMPASS-31 and Ewing's test also had the best correlation with respect to the severity of DAN (r = 0.587, p < 0.001). Ewing's test and COMPASS-31 had relatively good diagnostic values (AUC = 0.703 and 0.630, respectively) in the ROC analyses. Conclusions: COMPASS-31 and Ewing's test exhibit good diagnostic consistency and severity correlation for the diagnosis of DAN. Either test is suitable for the diagnosis of DAN and treatment follow-up.