Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records.

PURPOSE: Patients with epithelial ovarian cancer (EOC) have an elevated risk for venous thromboembolism (VTE). To assess the risk of VTE, models were developed by statistical or machine learning algorithms. However, few models have accommodated deep learning (DL) algorithms in realistic clinical settings. We aimed to develop a predictive DL model, exploiting rich information from electronic health records (EHRs), including dynamic clinical features and the presence of competing risks. METHODS: We extracted EHRs of 1,268 patients diagnosed with EOC from January 2007 through December 2017 at the National Cancer Center, Korea. DL survival networks using fully connected layers, temporal attention, and recurrent neural networks were adopted and compared with multi-perceptron-based classification models. Prediction accuracy was independently validated in the data set of 423 patients newly diagnosed with EOC from January 2018 to December 2019. Personalized risk plots displaying the individual interval risk were developed. RESULTS: DL-based survival networks achieved a superior area under the receiver operating characteristic curve (AUROC) between 0.95 and 0.98 while the AUROC of classification models was between 0.85 and 0.90. As clinical information benefits the prediction accuracy, the proposed dynamic survival network outperformed other survival networks for the test and validation data set with the highest time-dependent concordance index (0.974, 0.975) and lowest Brier score (0.051, 0.049) at 6 months after a cancer diagnosis. Our visualization showed that the interval risk fluctuating along with the changes in longitudinal clinical features. CONCLUSION: Adaption of dynamic patient clinical features and accounting for competing risks from EHRs into the DL algorithms demonstrated VTE risk prediction with high accuracy. Our results show that this novel dynamic survival network can provide personalized risk prediction with the potential to assist risk-based clinical intervention to prevent VTE among patients with EOC.

Saturated Fatty Acid Emulsions Open the Blood-Brain Barrier and Promote Drug Delivery in Rat Brains.

We performed this study to evaluate whether saturated fatty acid (SFA) emulsions affect the BBB and determine the duration of BBB opening, thereby promoting drug delivery to the brain. Butyric, valeric, caproic, enanthic, and caprylic acid emulsions were infused into the carotid artery of the rat model. We evaluated the BBB opening and drug delivery over time. The trypan blue and doxorubicin delivery studies were repeated from 30 min to 6 h. In the 1 h rats in each group, transmission electron microscopy (TEM) was performed to morphologically evaluate tight junctions, and the delivery of temozolomide was assessed by desorption electrospray ionization mass spectrometry. The ipsilateral hemisphere was positive for trypan blue staining in all the five SFA emulsion groups. In the valeric, enanthic, and caprylic acid emulsion groups, RGB ratios were significantly higher at 30 min and decreased thereafter. Doxorubicin delivery increased in all emulsion groups at all time points. Tight junctions were observed to be open in all groups. TMZ delivery was significantly higher in the ipsilateral hemisphere. In conclusion, intra-arterially infused SFA emulsions opened the BBB and promoted drug delivery within 30 min, which decreased thereafter. Therefore, SFA emulsions may aid BBB research and promote drug delivery to the brain.

Treatment-related cardiovascular events in patients with non-small cell lung cancer: Evidence from real-world data with a competing risks approach.

BACKGROUND: Understanding cancer treatment-related cardiovascular (CV) events is important for cancer care; however, comprehensive evaluation of CV events in patients with lung cancer is limited. This study aimed to assess the cumulative incidence and associated risks of various CV event types in patients with non-small cell lung cancer (NSCLC). METHODS: A total of 7868 individuals aged 40 years and older, recently diagnosed with NSCLC (2007-2018), were assessed with data obtained from the National Cancer Center, Korea. This study included nine types of CV events. A 2-year cumulative incidence function (CIF) of CV events was estimated, with death as a competing event. The associated risks were assessed by subdistribution hazard ratio (sHR) in the Fine-Gray competing risks model. RESULTS: CV events were observed in 7.8% of patients with NSCLC, with the most frequently observed types being atrial fibrillation and flutter (AF) (2.7%), venous thromboembolic disease (2.0%), and cerebrovascular disease (CeVD) (1.5%). Overall, all CV events were highest in the group treated with systemic therapy (CIF, 10.6%; 95% confidence interval [CI], 9.5%-11.8%), followed by those treated with surgery (CIF, 10.0%; 95% CI, 8.6%-11.6%); the incidence of AF (CIF, 5.7%; 95% CI, 4.6%-7.0%) was highest in patients treated with surgery. Individuals treated with systemic therapy were found to exhibit a higher CeVD risk than those treated with surgery (sHR, 4.12; 95% CI, 1.66-10.23). Among the patients who underwent surgery, those with lobectomy and pneumonectomy had a higher AF risk (vs. wedge resection/segmentectomy; sHR, 7.79; 95% CI, 1.87-32.42; sHR, 8.10; 95% CI, 1.60-40.89). CONCLUSIONS: These findings revealed treatment-related CV event risks in patients with NSCLC, which suggests that the risk of AF in surgery and CeVD in systemic therapy should be paid more attention to achieve a better prognosis and improve cancer survivorship outcomes. PLAIN LANGUAGE SUMMARY: Atrial fibrillation and flutter (AF) is the most common cardiovascular event, particularly at a high risk in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Patients receiving surgery with poor performance status, diagnosed with regional stage, and undergoing lobectomy or pneumonectomy are at a high risk of AF. Systemic/radiotherapy is associated with cerebrovascular and ischemic heart disease in patients with NSCLC.

Unsaturated free fatty acid emulsion infusion into carotid artery enhances drug delivery to the rat brain.

AIMS: To determine whether the blood-brain barrier (BBB) opens to enhance drug delivery during the acute stage of unsaturated fat embolism. METHODS: We infused oleic, linoleic, and linolenic acid emulsions through the right common carotid artery of rats, followed by trypan blue for gross and lanthanum for electron microscopic (EM) examination. Doxorubicin and temozolomide were also administered, and then the rats were euthanized at 30 min, 1 h, and 2 h. Trypan blue hue was analyzed to semiquantitatively measure BBB opening. Desorption electrospray ionization-mass spectrometry (DESI-MS) imaging was used to evaluate drug delivery. RESULTS: Trypan blue staining observed in each group 30 min after emulsion infusion increased at 1 h and decreased after 2 h in the oleic acid group. The linoleic and linolenic acid groups showed weak staining over time. The hue and trypan blue analysis results were corroborative. EM showed tight junction opening, whereas DESI-MS imaging showed increased doxorubicin and temozolomide signal intensities in ipsilateral hemispheres of all three groups. CONCLUSION: We demonstrated that oleic, linoleic, and linolenic acid emulsions opened the BBB, promoting drug delivery to the brain. Hue analysis and DESI-MS imaging are appropriate for analysis of doxorubicin and temozolomide concentrations in brain tissue.

[Development of Rabbit Brain Tumor Model Using VX2 Cells and Verification with the MRI in Neuroradiologic Research]. / Neuroradiology 연구를 위한 VX2 세포를 이용한 í† ë¼ ë‡Œì¢ ì–‘ 모델 ì œìž‘ê³¼ MRI를 이용한 검증.

Purpose: To evaluate the development, location, and volume of a VX2 carcinoma using four inoculation methods in a rabbit brain. Materials and Methods: Inoculation of a VX2 cell suspension was performed 1) on the appointed day, 2) seven days after storing a VX2 carcinoma in a freezer or 3) seven days after storing a VX2 carcinoma in a deep freezer after sacrificing the donor rabbits. 4) Without sacrificing the rabbits, the VX2 cell suspension was obtained using a gun biopsy, inoculation was performed on the appointed day. MR imaging was performed 10 days after inoculation. Brain tissues were obtained the day after. The development, location, and volume of the tumor were evaluated. Results: Seventeen of the 18 rabbits inoculated on the appointed day developed tumors (average tumor volume, 106.32 mm3). One of five inoculated seven days after storing the VX2 tumor in the freezer, and three of five inoculated seven days after storing the VX2 tumor in the deep freezer developed tumors. Inoculation with a VX2 cell suspension obtained with a gun biopsy from five rabbits revealed development of tumors in only two rabbits. The tumors mostly developed in the superficial cortex. Conclusion: TVX2 rabbit brain tumor model is easy to develop and revealed variable reproducibility. This model can be applicable in radiologic imaging, treatment planning, interventional treatment and drug delivery research. VX2 cell can be successfully innoculated into the brain using variable methods under researcher's variable conditions.

Effects of sodium diacetate and microbial inoculants on fermentation of forage rye.

Rye (Secale cereale L.) is a valuable annual forage crop in Korea but there is limited information about the impact of chemical and biological additives on fermentation characteristics of the crop. This experiment was conducted to investigate fermentation dynamics of wilted forage rye treated with the following six additives; control (no additive), sodium diacetate applied at 3 g/kg wilted forage weight (SDA3), 6 g/kg wilted forage weight (SDA6), inoculations (106 CFU/g wilted forage) of Lactobacillus plantarum (LP), L. buchneri (LB), or LP+LB. The ensiled rye sampled at 1, 2, 3, 5, 10, 20, 30, and 45 days indicated that the acidification occurred fast within five days of storage than the rest of the storage period. The microbial inoculants decline the pH of ensiled forage, more rapidly than the control or SDA treated, which accompanied by the decrease of water-soluble carbohydrates and increase of lactic acid. Compared with the control silage, all treatments suppressed ammonia-nitrogen formation below to 35 g/kg DM throughout the sampling period. Suppression of total microbial counting occurred in SDA6, LP, and LP + LB. The lactic acid production rates were generally higher in microbial inoculation treatments. Acetic acid concentration was lowest in the LP-treated silage and highest in the SDA- and LB-treated silages. The in vitro dry matter (DM) digestibility and total digestible nutrients were the highest in the silage treated with SDA (6 g/kg) at day 45 of ensiling. Based on lower ammonia-nitrogen concentrations and higher feed value, ensiling forage rye treated with SDA at 6 g/kg is promising through enhanced silage quality.

Heterogeneity Assessment of Kenaf Breeding Field through Spatial Dependence Analysis on Crop Growth Status Map Derived by Unmanned Aerial Vehicle.

The investigation of quantitative phenotypic traits resulting from the interaction between targeted genotypic traits and environmental factors is essential for breeding selection. Therefore, plot-wise controlled environmental factors must be invariable for accurate identification of phenotypes. However, the assumption of homogeneous variables within the open-field is not always accepted, and requires a spatial dependence analysis to determine whether site-specific environmental factors exist. In this study, spatial dependence within the kenaf breeding field was assessed in a geo-tagged height map derived from an unmanned aerial vehicle (UAV). Local indicators of spatial autocorrelation (LISA) were applied to the height map using Geoda software, and the LISA map was generated in order to recognize the existence of kenaf height status clusters. The spatial dependence of the breeding field used in this study appeared in a specific region. The cluster pattern was similar to the terrain elevation pattern of this field and highly correlated with drainage capacity. The cluster pattern could be utilized to design random blocks based on regions that have similar spatial dependence. We confirmed the potential of spatial dependence analysis on a crop growth status map, derived by UAV, for breeding strategy design with a tight budget.

Decision-tree-based ion-specific dosing algorithm for enhancing closed hydroponic efficiency and reducing carbon emissions.

The maintenance of ion balance in closed hydroponic solutions is essential to improve the crop quality and recycling efficiency of nutrient solutions. However, the absence of robust ion sensors for key ions such as P and Mg and the coupling of ions in fertilizer salts render it difficult to effectively manage ion-specific nutrient solutions. Although ion-specific dosing algorithms have been established, their effectiveness has been inadequately explored. In this study, a decision-tree-based dosing algorithm was developed to calculate the optimal volumes of individual nutrient stock solutions to be supplied for five major nutrient ions, i.e., NO3, K, Ca, P, and Mg, based on the concentrations of NO3, K, and Ca and remaining volume of the recycled nutrient solution. In the performance assessment based on five nutrient solution samples encompassing the typical concentration ranges for leafy vegetable cultivation, the ion-selective electrode array demonstrated feasible accuracies, with root mean square errors of 29.5, 10.1, and 6.1 mg·L-1 for NO3, K, and Ca, respectively. In a five-step replenishment test involving varying target concentrations and nutrient solution volumes, the system formulated nutrient solutions according to the specified targets, exhibiting average relative errors of 10.6 ± 8.0%, 7.9 ± 2.1%, 8.0 ± 11.0%, and 4.2 ± 3.7% for the Ca, K, and NO3 concentrations and volume of the nutrient solution, respectively. Furthermore, the decision tree method helped reduce the total fertilizer injections and carbon emissions by 12.8% and 20.6% in the stepwise test, respectively. The findings demonstrate that the decision-tree-based dosing algorithm not only enables more efficient reuse of nutrient solution compared to the existing simplex method but also confirms the potential for reducing carbon emissions, indicating the possibility of sustainable agricultural development.

An early interactive human coaching via a mobile application to improve quality of life in patients who underwent gastrectomy for gastric cancer: Design and protocol of a randomized controlled trial.

BACKGROUND: After gastrectomy, patients may experience the postgastrectomy syndrome and face difficulties adapting to everyday diet. Recently, human health coaching via a mobile application (app) has been used for obese patients or patients with chronic diseases, with significant improvements in clinical outcomes. The aim of this study is to evaluate and compare the effects of human health coaching via a mobile app and conventional face-to-face counseling in patients who underwent gastrectomy for gastric cancers. METHODS: This study is a single-institution, prospective randomized controlled trial comparing the mobile health and face-to-face counselling groups. After randomization, participants assigned to the mobile health coaching group will receive health coaching via a mobile app for 3 months after discharge, and the assigned coaches will provide personalized advice based on the self-recorded health data. Participants in the face-to-face group will have 1- and 3-months postoperative dietary consultations with a clinical dietitian. The primary endpoint is the food restriction score on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-STO22, and secondary endpoints included all other quality of life scale scores and nutritional parameters. The calculated sample size is 180, and the outcomes will be measured until 1-year post-surgery. SIGNIFICANCE: This study will show the efficacy of human health coaching via a mobile app on dietary adaptation in patients who underwent gastrectomy. A relational approach based on personal data and timely intervention using a mobile platform could reduce patients' trial and error and improve quality of life. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04394585, Registered 19 May, 2020 -Retrospectively registered, http://clinicaltrials.gov/ct2/show/NCT040394585.

Estimation of Greenhouse Lettuce Growth Indices Based on a Two-Stage CNN Using RGB-D Images.

Growth indices can quantify crop productivity and establish optimal environmental, nutritional, and irrigation control strategies. A convolutional neural network (CNN)-based model is presented for estimating various growth indices (i.e., fresh weight, dry weight, height, leaf area, and diameter) of four varieties of greenhouse lettuce using red, green, blue, and depth (RGB-D) data obtained using a stereo camera. Data from an online autonomous greenhouse challenge (Wageningen University, June 2021) were employed in this study. The data were collected using an Intel RealSense D415 camera. The developed model has a two-stage CNN architecture based on ResNet50V2 layers. The developed model provided coefficients of determination from 0.88 to 0.95, with normalized root mean square errors of 6.09%, 6.30%, 7.65%, 7.92%, and 5.62% for fresh weight, dry weight, height, diameter, and leaf area, respectively, on unknown lettuce images. Using red, green, blue (RGB) and depth data employed in the CNN improved the determination accuracy for all five lettuce growth indices due to the ability of the stereo camera to extract height information on lettuce. The average time for processing each lettuce image using the developed CNN model run on a Jetson SUB mini-PC with a Jetson Xavier NX was 0.83 s, indicating the potential for the model in fast real-time sensing of lettuce growth indices.

Effects of sodium diacetate or microbial inoculants on aerobic stability of wilted rye silage.

OBJECTIVE: The primary goal was to identify the effectiveness of chemical or biological additives in delaying the deterioration of early-harvested wilted rye silage after exposure to air. METHODS: Rye harvested as a whole plant at the early heading stage was wilted for 24 h. The wilted forage was divided into treatments including sodium diacetate (SDA) at 3 (SDA3) and 6 g/kg (SDA6), Lactobacillus plantarum (LP), L. buchneri (LB), or their equal mixture (LP+LB) at 1×106 colony-forming unit/g fresh matter. RESULTS: After 60 d of conservation in 20-L silos, lactic acid was greater in LP and LP+LB silages than other treatments (102 vs 90.2 g/kg dry matter [DM]). Acetic acid was greatest in SDA6 (32.0 g/kg DM) followed by LB (26.1 g/kg DM) and was lowest in LP treatment (4.73 g/kg DM). Silage pH was lower with microbial inoculation and the lowest and highest values were observed in LP and untreated silages, respectively. After 60 d, neutral detergent fiber concentration was lowest in SDA6 silages, resulting in the greatest in vitro DM digestibility (846 g/kg DM). Aerobic stability was longest in SDA6 (176 h) followed by LB treatment (134 h). Instability after aerobiosis was greatest in LP silages (68 h), about 8 h less than untreated silages. After aerobic exposure, yeast and mold numbers were lowest in SDA6 silages, resulting in DM loss minimization. Exhaustion of acetic acid and lactic acid after aerobic exposure was lowest with SDA6 but greatest with untreated and LP silages. CONCLUSION: Treatment of early-cut wilted rye forage with SDA at 6 g/kg resulted in silages with higher feeding value and fermentation quality, and substantially delayed deterioration after aerobic exposure, potentially qualifying SDA at this load for promotion of silage quality and delaying aerobic spoilage of early-harvested (low DM) rye forage.

Comparison of Energy and Macronutrients Between a Mobile Application and a Conventional Dietary Assessment Method in Korea.

BACKGROUND: The use of mobile apps for dietary evaluation avoids some of the disadvantages of costly and time-consuming traditional diet assessment. However, few studies have compared dietary intake data in smartphone apps with a conventional diet assessment. OBJECTIVE: This study aimed to compare the dietary data collected on energy and macronutrients (proteins, fats, and carbohydrates) consumed for 3 nonconsecutive days using both a mobile application (Noom) and a conventional dietary assessment tool (CAN Pro). DESIGN: This was a cross-sectional study. PARTICIPANTS/SETTING: A total of 119 healthy adults (68 males and 51 females) aged 19 to 65 years were recruited from the National Cancer Center in Korea between May and September 2019. MAIN OUTCOME MEASURES: The mean daily energy and macronutrient intake data were obtained for the dietary intakes consumed for 3 nonconsecutive days using Noom and CAN Pro. STATISTICAL ANALYSIS PERFORMED: The estimates of energy and macronutrient intake between the two tools were compared using correlation coefficients and cross-classification. RESULTS: Although mean daily fat intake and percent total energy from carbohydrate estimated by Noom were comparable with values provided by CAN Pro, mean daily estimated energy intake (kcal), protein (g, percent total energy), and carbohydrate (g) were significantly higher with Noom than with CAN Pro. The correlation coefficients ranged from 0.79 to 0.99 for crude intake and from 0.77 to 0.88 for energy-adjusted values of intake after adjustment for sex and age. The percentages of participants classified into quartiles of "exact agreement and plus adjacent" varied between 95% and 99% for crude intake and between 93% and 97% for energy-adjusted values of intake. CONCLUSIONS: The findings indicate that Noom may be useful for monitoring the dietary intake of energy and macronutrients and reducing workload compared with a traditional dietary assessment in Korea. However, further research is needed to assess the validity and usability of Noom for estimating intake of micronutrients and other dietary components.

Erratum: Isolated Vestibular Syndrome With "Double-Panda" Sign in CNS Lymphoma.

This corrects the article on p. 111 in vol. 18, PMID: 35021288.

Reduction malarplasty using a simulated surgical guide for asymmetric/prominent zygoma.

BACKGROUND: The present study introduces a reduction malarplasty using a three-dimensional (3D)-printed surgical guide and evaluates the guide's technical applicability. METHODS: Twenty malarplasties were performed for 12 subjects with zygomatic asymmetry/prominency using the current method. 3D reconstruction of the craniomaxillofacial region and fine dental occlusion was made with image data from computed tomograpy and dental scanning. A computer-assisted surgical simulation was performed for reduction malarplasty and a surgical guide was designed for later 3D printing. The manufactured surgical guide was introduced to the operation field to guide the surgery; its surgical accuracy was confirmed by comparing five corresponding points from preoperative simulation and postoperative data. RESULTS: We successfully performed the reduction malarplasty with the surgical guide. The accuracy level of surgery fell to 0.93 mm of total median difference for the corresponding zygoma points of preoperative simulations and postoperative zygoma. The anterior and upper points showed less error level (0.59 and 0.73 mm difference, respectively) than did other points. CONCLUSIONS: We developed a computer-assisted surgical technique using a surgical guide for asymmetrical/prominent zygoma which proved to be simple, practical, and accurate; it is expected to help surgeons perform reduction malarplasty with ease and accuracy.

Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network.

High-precision position estimations of agricultural mobile robots (AMRs) are crucial for implementing control instructions. Although the global navigation satellite system (GNSS) and real-time kinematic GNSS (RTK-GNSS) provide high-precision positioning, the AMR accuracy decreases when the signals interfere with buildings or trees. An improved position estimation algorithm based on multisensor fusion and autoencoder neural network is proposed. The multisensor, RTK-GNSS, inertial-measurement-unit, and dual-rotary-encoder data are fused with Extended Kalman filter (EKF). To optimize the EKF noise matrix, the autoencoder and radial basis function (ARBF) neural network was used for modeling the state equation noise and EKF measurement equation. A multisensor AMR test platform was constructed for static experiments to estimate the circular error probability and twice-the-distance root-mean-squared criteria. Dynamic experiments were conducted on road, grass, and field environments. To validate the robustness of the proposed algorithm, abnormal working conditions of the sensors were tested on the road. The results showed that the positioning estimation accuracy was improved compared to the RTK-GNSS in all three environments. When the RTK-GNSS signal experienced interference or rotary encoders failed, the system could still improve the position estimation accuracy. The proposed system and optimization algorithm are thus significant for improving AMR position prediction performance.

Evaluation of forage production, feed value, and ensilability of proso millet (Panicum miliaceum L.).

Whole-plant corn (Zea may L.) and sorghum-sudangrass hybrid [Sorghum bicolor (L.) Moench] are major summer crops that can be fed as direct-cut or silage. Proso millet is a short-season growing crop with distinct agronomic characteristics that can be productive in marginal lands. However, information is limited about the potential production, feed value, and ensilability of proso millet forage. We evaluated proso millet as a silage crop in comparison with conventional silage crops. Proso millet was sown on June 8 and harvested on September 5 at soft-dough stage. Corn and sorghum-sudangrass hybrid were planted on May 10 and harvested on September 10 at the half milk-line and soft-dough stages, respectively. The fermentation was evaluated at 1, 2, 3, 5, 10, 15, 20, 30, and 45 days after ensiling. Although forage yield of proso millet was lower than corn and sorghum-sudangrass hybrid, its relative feed value was greater than sorghum-sudangrass hybrid. Concentrations of dry matter (DM), crude protein, and water-soluble carbohydrate decreased commonly in the ensiling forage crops. The DM loss was greater in proso millet than those in corn and sorghum-sudangrass hybrid. The in vitro dry matter digestibility declined in the forage crops as fermentation progressed. In the early stages of fermentation, pH dropped rapidly, which was stabilized in the later stages. Compared to corn and sorghum-sudangrass hybrid, the concentration of ammonia-nitrogen was greater in proso millet. The count of lactic acid bacteria reached the maximum level on day 10, with the values of 6.96, 7.77, and 6.95 Log10 CFU/g fresh weight for proso millet, corn, and sorghum-sudangrass hybrid, respectively. As ensiling progressed, the concentrations of lactic acid and acetic acid of the three crops increased and lactic acid proportion became higher in the order of sorghum-sudangrass hybrid, corn, and proso millet. Overall, the shorter, fast-growing proso millet comparing with corn and sorghum-sudangrass hybrid makes this forage crop an alternative option, particularly in areas where agricultural inputs are limited. However, additional research is needed to evaluate the efficacy of viable strategies such as chemical additives or microbial inoculants to minimize ammonia-nitrogen formation and DM loss during ensiling.

The Role of Decreased Cortical Thickness and Volume of Medial Temporal Lobe Structures in Predicting Incident Psychosis in Patients With Alzheimer's Disease: A Prospective Longitudinal MRI Study.

OBJECTIVE: To investigate the effect of decreased cortical thickness or volume of medial temporal lobe structures on the risk of incident psychosis in patients with AD. DESIGN, SETTING, AND PARTICIPANTS: This hospital-based prospective longitudinal study enrolled 109 patients with AD. All patients with AD were evaluated at 3-month intervals to investigate the effect of decreased cortical thickness or volume of medial temporal lobe structures on the risk of incident psychosis in patients with AD. OUTCOME MEASURE: The main outcome measure was time-to-progression from AD to incident psychosis. The thickness or volume of medial temporal lobe structures (i.e., the hippocampus, entorhinal cortex, and parahippocampus) were measured using magnetic resonance imaging and the Freesurfer automated segmentation pipeline at baseline. RESULTS: Multivariate Cox proportional hazards regression analysis revealed that a decreased cortical thickness or volume of medial temporal region was associated with a higher risk of incident psychosis in patients with AD. The hazard ratios for decreased cortical thickness of the left entorhinal cortex and decreased cortical volume of the right hippocampus were 4.291 (95% confidence interval [CI], 1.196-15.384) and 2.680 [(CI, 1.003-1.196]), respectively. CONCLUSION: Our study revealed that decreased cortical thickness or volume of medial temporal sub-regions is a risk factor for incident psychosis in patients with AD. A careful assessment of the thickness or volume of the medial temporal lobe structures in AD may improve early detection and intervention of psychosis in AD.

The Relationship of Plasma Transthyretin Level with Global or Regional Amyloid Beta Burden in Subjects with Amnestic Mild Cognitive Impairment: Cross-Sectional Amyloid PET Study.

Background: To investigate the relationships of plasma transthyretin levels with amyloid beta deposition and medial temporal atrophy in amnestic mild cognitive impairment. Methods: This is a cross-sectional study of association of subjects with amnestic mild cognitive impairment. Plasma transthyretin levels, brain magnetic resonance imaging, and 18F-florbetaben positron emission tomography were simultaneously measured in subjects with amnestic mild cognitive impairment. Results: Plasma transthyretin levels were positively associated with amyloid beta deposition in global (r = 0.394, P = .009), frontal cortex (r = 0.316, P = .039), parietal cortex (r = 0.346, P = .023), temporal cortex (r = 0.372, P = .014), occipital cortex (r = 0.310, P = .043), right posterior cingulate (r = 0.350, P = .021), left precuneus (r = 0.314, P = .040), and right precuneus (r = 0.398, P = .008). No association between plasma transthyretin level and medial temporal sub-regional atrophies was found. Conclusions: Our findings of positive association of plasma transthyretin levels with global and regional amyloid beta burden suggest upregulation of transthyretin level as a reactive response to amyloid beta deposition during the early stages of the Alzheimer's disease process.

Reduced Thickness of the Anterior Cingulate Cortex as a Predictor of Amnestic-Mild Cognitive Impairment Conversion to Alzheimer's Disease with Psychosis.

BACKGROUND: A long-term follow-up study in patients with amnestic mild cognitive impairment (aMCI) is needed to elucidate the association between regional brain volume and psychopathological mechanisms of Alzheimer's disease with psychosis (AD + P). OBJECTIVE: The purpose of this study was to investigate the effect of the thickness of the angular cingulate cortex (ACC) on the risk of AD + P conversion in patients with aMCI. METHODS: This was a hospital-based prospective longitudinal study including 174 patients with aMCI. The main outcome measure was time-to-progression from aMCI to AD + P. Subregions of the ACC (rostral ACC, rACC; caudal ACC, cACC) and hippocampus (HC) were measured as regions of interest with magnetic resonance imaging and the Freesurfer analysis at baseline. Survival analysis with time to incident AD + P as an event variable was calculated with Cox proportional hazards models using the subregions of the ACC and HC as a continuous variable. RESULTS: Cox proportional hazard analyses showed that the risk of AD + P was associated with sub-regional ACC thickness but not HC volume: reduced cortical thickness of the left cACC (HR [95%CI], 0.224 [0.087-0.575], p = 0.002), right cACC (HR [95%CI], 0.318 [0.132-0.768], p = 0.011). This association of the cACC with the risk of AD also remained significant when adjusted for HC volume. CONCLUSION: We found that reduced cortical thickness of the cACC is a predictor of aMCI conversion to AD + P, independent of HC, suggesting that the ACC plays a vital role in the underlying pathogenesis of AD + P.