Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.

OBJECTIVES: Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The study aimed to construct machine learning models to predict colistin-induced nephrotoxicity in patients with multidrug-resistant Gram-negative infection. METHODS: Patients receiving colistin from three hospitals in the Clinical Research Database were included. Data were divided into a derivation cohort (2011-2017) and a temporal validation cohort (2018-2020). Fifteen machine learning models were established by categorical boosting, light gradient boosting machine and random forest. Classifier performances were compared by the sensitivity, F1 score, Matthews correlation coefficient (MCC), area under the receiver operating characteristic (AUROC) curve, and area under the precision-recall curve (AUPRC). SHapley Additive exPlanations plots were drawn to understand feature importance and interactions. RESULTS: The study included 1392 patients, with 360 (36.4%) and 165 (40.9%) experiencing nephrotoxicity in the derivation and temporal validation cohorts, respectively. The categorical boosting with oversampling achieved the highest performance with a sensitivity of 0.860, an F1 score of 0.740, an MCC of 0.533, an AUROC curve of 0.823, and an AUPRC of 0.737. The feature importance demonstrated that the days of colistin use, cumulative dose, daily dose, latest C-reactive protein, and baseline haemoglobin were the most important risk factors, especially for vulnerable patients. A cutoff colistin dose of 4.0 mg/kg body weight/d was identified for patients at higher risk of nephrotoxicity. CONCLUSIONS: Machine learning techniques can be an early identification tool to predict colistin-induced nephrotoxicity. The observed interactions suggest a modification in dose adjustment guidelines. Future geographic and prospective validation studies are warranted to strengthen the real-world applicability.

Is use of a long-term proton pump inhibitor or histamine-2 receptor antagonist a risk factor for iron-deficiency anaemia in Taiwan? A neglected clinical drug-drug interaction.

BACKGROUND: Proton pump inhibitors (PPIs) and histamine-2 receptor (H2) antagonists change the gastric pH and reduce the intestinal absorption of nonheme iron. Case reports and case-control studies have demonstrated that absorption of iron is affected by gastric acidity, but the clinical importance of these drug-drug interactions has remained uncertain. OBJECTIVES: The present case-control study employed 2 million longitudinal claims in 2011-2018 in the Taiwan National Health Insurance Research Database to investigate the impact of PPIs/H2 antagonists on the occurrence of iron-deficiency anaemia (IDA). METHODS: The present study retrospectively compared exposure to PPIs/H2 antagonists for 1 year among 5,326 cases with IDA and 21,304 matched controls. The postdiagnosis prescribing pattern was also calculated to understand current practice. RESULTS: Long-term (≥2 month) use of PPIs/H2 antagonists resulted in a higher risk of developing IDA than noncontinuous use/nonuse of those drugs (adjusted odds ratio [aOR] = 2.36, 95% confidence interval [CI] = 1.94-2.86, P < 0.001). There were significant changes in the postdiagnosis prescribing patterns of PPIs/H2 antagonists. The risk of developing IDA remained significant in the female subgroup (aOR = 2.16, 95% CI = 1.73-2.70, P < 0.001) and was even more prominent in those aged ≥ 50 years (aOR = 2.68, 95% CI = 1.94-3.70, P < 0.05). CONCLUSIONS: This study found that long-term use of PPIs/H2 antagonists increased the risk of developing IDA, and there was strong evidence of prescription pattern adjustments postdiagnosis. Physicians and pharmacists should be aware of this risk when patients are expected to take or have been taking PPIs/H2 antagonists for the long term.

Proton pump inhibitors (PPIs) and histamine-2 receptor (H2) antagonists, 2 kinds of gastric suppressants commonly used for gastroesophageal reflux disease, decrease iron absorption in the gut and thus increase the risk of developing iron-deficiency anaemia (IDA). We constructed a retrospective matched case-control study within the Taiwan National Health Insurance Research Database. The longer period of PPIs/H2 antagonists used, the higher risk of IDA was, with the highest risk in female elderly groups (adjusted odds ratio = 2.68 in females aged ≥ 50). PPI users had a higher risk than H2 antagonist users during the 1-year follow-up. The prescription patterns postdiagnosis of IDA witnessed considerable drops for both groups, with less than a 10th of original users remaining the usages (1.72% and 9.85% taking PPIs and H2 antagonists within 90 days after receiving a diagnosis, respectively). Physicians and pharmacists should be aware of the risk of developing IDA in patients currently undergoing or expected to take long-term gastric acid suppressants.

Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation.

BACKGROUND: Machine learning offers new solutions for predicting life-threatening, unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches for adverse-effect prediction without time-series consideration of features have yielded suboptimal predictions. Machine learning algorithms with multiple data sets at different time points may generate better performance in predicting adverse effects. OBJECTIVE: We aimed to develop and validate machine learning models for forecasting individualized amiodarone-induced thyroid dysfunction risk and to optimize a machine learning-based risk stratification scheme with a resampling method and readjustment of the clinically derived decision thresholds. METHODS: This study developed machine learning models using multicenter, delinked electronic health records. It included patients receiving amiodarone from January 2013 to December 2017. The training set was composed of data from Taipei Medical University Hospital and Wan Fang Hospital, while data from Taipei Medical University Shuang Ho Hospital were used as the external test set. The study collected stationary features at baseline and dynamic features at the first, second, third, sixth, ninth, 12th, 15th, 18th, and 21st months after amiodarone initiation. We used 16 machine learning models, including extreme gradient boosting, adaptive boosting, k-nearest neighbor, and logistic regression models, along with an original resampling method and 3 other resampling methods, including oversampling with the borderline-synthesized minority oversampling technique, undersampling-edited nearest neighbor, and over- and undersampling hybrid methods. The model performance was compared based on accuracy; Precision, recall, F1-score, geometric mean, area under the curve of the receiver operating characteristic curve (AUROC), and the area under the precision-recall curve (AUPRC). Feature importance was determined by the best model. The decision threshold was readjusted to identify the best cutoff value and a Kaplan-Meier survival analysis was performed. RESULTS: The training set contained 4075 patients from Taipei Medical University Hospital and Wan Fang Hospital, of whom 583 (14.3%) developed amiodarone-induced thyroid dysfunction, while the external test set included 2422 patients from Taipei Medical University Shuang Ho Hospital, of whom 275 (11.4%) developed amiodarone-induced thyroid dysfunction. The extreme gradient boosting oversampling machine learning model demonstrated the best predictive outcomes among all 16 models. The accuracy; Precision, recall, F1-score, G-mean, AUPRC, and AUROC were 0.923, 0.632, 0.756, 0.688, 0.845, 0.751, and 0.934, respectively. After readjusting the cutoff, the best value was 0.627, and the F1-score reached 0.699. The best threshold was able to classify 286 of 2422 patients (11.8%) as high-risk subjects, among which 275 were true-positive patients in the testing set. A shorter treatment duration; higher levels of thyroid-stimulating hormone and high-density lipoprotein cholesterol; and lower levels of free thyroxin, alkaline phosphatase, and low-density lipoprotein were the most important features. CONCLUSIONS: Machine learning models combined with resampling methods can predict amiodarone-induced thyroid dysfunction and serve as a support tool for individualized risk prediction and clinical decision support.

Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis.

BACKGROUND AND OBJECTIVE: The specific aim of this study is to develop machine learning models as a clinical approach for personalized treatment of osteoporosis. The model performance on outcome prediction was compared between four machine learning algorithms. METHODS: Retrospective, electronic clinical data for patients with suspected or confirmed osteoporosis treated at Wan Fang Hospital between 2011 to 2018 were used as inputs for building the following predictive machine learning models,i.e., artificial neural network (ANN), random forest (RF), support vector machine (SVM) and logistic regression (LR) models. The predicted outcome was defined as an increase/decrease in T-score after treatment. A genetic algorithm was employed to select relevant variables as input features for each model; the leave-one-out method was applied for model building and internal validation. The model with best performance was selected by a separate set of testing. Area under the receiver operating characteristic curve, accuracy, precision, sensitivity and F1 score were calculated to evaluate model performance. Main analysis for all the patients with subclinical or confirmed osteoporosis and subgroup analysis for the patients with confirmed osteoporosis (T score < -2.5) were carried out in this study. RESULTS: A genetic algorithm was employed to select 12 to 18 features from all 33 variables for the four models. No difference was found in accuracy (ANN, 71.7%; LR, 70.0%; RF, 75.0%; SVM, 66.7%), precision (ANN, 80.0%; LR, 59.3%; RF, 70.0%; SVM, 63.6%), and AUC (ANN, 0.709; LR, 0.731; RF, 0.719; SVM, 0.702) among the ANN, LR, RF and SVM models. Main analysis in performance revealed significant recall in the LR model, as compared to ANN and SVM model; while subgroup revealed significant recall in ANN model, compared to LR and SVM model. CONCLUSIONS: Machine learning-based models hold potential in forecasting the outcomes of treatment for osteoporosis via early initiation of first-line therapy for patients with subclinical disease; or a switch to second-line treatment for patients with a high risk of impending treatment failure. This convenient approach can assist clinicians in adjusting treatment tailored to individual patient for prevention of disease progression or ineffective therapy.

How platinum-induced nephrotoxicity occurs? Machine learning prediction in non-small cell lung cancer patients.

BACKGROUND AND OBJECTIVE: Platinum-induced nephrotoxicity is a severe and unexpected adverse drug reaction that could lead to treatment failure in non-small cell lung cancer patients. Better prediction and management of this nephrotoxicity can increase patient survival. Our study aimed to build up and compare the best machine learning models with clinical and genomic features to predict platinum-induced nephrotoxicity in non-small cell lung cancer patients. METHODS: Clinical and genomic data of patients undergoing platinum chemotherapy at Wan Fang Hospital were collected after they were recruited. Twelve models were established by artificial neural network, logistic regression, random forest, and support vector machine with integrated, clinical, and genomic modes. Grid search and genetic algorithm were applied to construct the fine-tuned model with the best combination of predictive hyperparameters and features. Accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve were calculated to compare the performance of the 12 models. RESULTS: In total, 118 patients were recruited for this study, among which 28 (23.73%) were experiencing nephrotoxicity. Machine learning models with clinical and genomic features achieved better prediction performances than clinical or genomic features alone. Artificial neural network with clinical and genomic features demonstrated the best predictive outcomes among all 12 models. The average accuracy, precision, recall, F1 score and area under the receiver operating characteristic curve of the artificial neural network with integrated mode were 0.923, 0.950, 0.713, 0.808 and 0.900, respectively. CONCLUSIONS: Machine learning models with clinical and genomic features can be a preliminary tool for oncologists to predict platinum-induced nephrotoxicity and provide preventive strategies in advance.

Inhibiting viral replication and prolonging survival of hosts by attenuating stress responses to viral infection.

Viruses are obligate intracellular parasites relying on host cells to obtain biosynthetic precursors and energy to successfully infect the host. The metabolic profile of the host cell is known to be altered in response to viral infection to satisfy the resources demanded during viral replication. Previous data of ours showed that white spot syndrome virus (WSSV) elicited in a crustacean host (Procambarus clarkii) a rapid and long-lasting release of crustacean hyperglycemic hormone (CHH), a well-known carbohydrate-regulating and stress response-mediating endocrine hormone. Therefore, the WSSV-enhanced release of CHH could be responsible at least in part for the metabolic alterations in the WSSV-challenged host. To investigate the possible metabolic roles of CHH in the host-parasite interaction, we studied whether silencing CHH gene expression could inhibit WSSV propagation in tissues and reduce the mortality of the WSSV-infected animals. Data presented in this study showed that CHH gene silencing indeed resists the WSSV infection. Injection of CHH dsRNA at the dosage of 140 µg/g BW caused significant decreases of viral copy number in tissues of WSSV-infected host, particularly showing a pronounced effect in the endodermal tissues (including hepatopancreas and gastrolith disk). Furthermore, results from the cumulative mortality showed that the treatment of CHH dsRNA delayed death from WSSV. Injection of CHH dsRNA at the dosages of 70, 17, and 10 µg/ g BW significantly extended the mean survival time. Together, this study concludes that the silencing of the CHH gene does have an inhibitory effect on the replication of the white spot syndrome virus and can assist the host to mitigate the invasion of WSSV, through attenuating CHH-mediated stress responses.

Social Media-Delivered Patient Education to Enhance Self-management and Attitudes of Patients with Type 2 Diabetes During the COVID-19 Pandemic: Randomized Controlled Trial.

BACKGROUND: The use of mobile health technologies has been necessary to deliver patient education to patients with diabetes during the COVID-19 pandemic. OBJECTIVE: This open-label randomized controlled trial evaluated the effects of a diabetes educational platform-Taipei Medical University-LINE Oriented Video Education-delivered through a social media app. METHODS: Patients with type 2 diabetes were recruited from a clinic through physician referral. The social media-based program included 51 videos: 10 about understanding diabetes, 10 about daily care, 6 about nutrition care, 21 about diabetes drugs, and 4 containing quizzes. The intervention group received two or three videos every week and care messages every 2 weeks through the social media platform for 3 months, in addition to usual care. The control group only received usual care. Outcomes were measured at clinical visits through self-reported face-to-face questionnaires at baseline and at 3 months after the intervention, including the Simplified Diabetes Knowledge Scale (true/false version), the Diabetes Care Profile-Attitudes Toward Diabetes Scales, the Summary of Diabetes Self-Care Activities, and glycated hemoglobin (HbA1c) levels. Health literacy was measured at baseline using the Newest Vital Sign tool. Differences in HbA1c levels and questionnaire scores before and after the intervention were compared between groups. The associations of knowledge, attitudes, and self-care activities with health literacy were assessed. RESULTS: Patients with type 2 diabetes completed the 3-month study, with 91 out of 181 (50.3%) patients in the intervention group and 90 (49.7%) in the control group. The change in HbA1c did not significantly differ between groups (intervention group: mean 6.9%, SD 0.8% to mean 7.0%, SD 0.9%, P=.34; control group: mean 6.7%, SD 0.6% to mean 6.7%, SD 0.7%, P=.91). Both groups showed increased mean knowledge scores at 12 weeks, increasing from 68.3% (SD 16.4%) to 76.7% (SD 11.7%; P<.001) in the intervention group and from 64.8% (SD 18.2%) to 73.2% (SD 12.6%; P<.001) in the control group. Positive improvements in attitudes and self-care activities were only observed in the intervention group (attitudes: mean difference 0.2, SD 0.5, P=.001; self-care activities: mean difference 0.3, SD 1.2, P=.03). A 100% utility rate was achieved for 8 out of 21 (38%) medication-related videos. Low health literacy was a significant risk factor for baseline knowledge scores in the intervention group, with an odds ratio of 2.80 (95% CI 1.28-6.12; P=.01); this became insignificant after 3 months. CONCLUSIONS: The social media-based program was effective at enhancing the knowledge, attitudes, and self-care activities of patients with diabetes. This intervention was also helpful for patients with low health literacy in diabetes knowledge. The program represents a potentially useful tool for delivering diabetes education to patients through social media, especially during the COVID-19 pandemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT04876274; https://clinicaltrials.gov/ct2/show/results/NCT04876274.

Calcium signaling and regulation of ecdysteroidogenesis in crustacean Y-organs.

Crustacean Y-organs secrete ecdysteroid molting hormones. Ecdysteroids are released in increased amount during premolt, circulate in hemolymph, and stimulate the events in target cells that lead to molting. During much of the molting cycle, ecdysteroid production is suppressed by molt-inhibiting hormone (MIH), a peptide neurohormone produced in the eyestalks. The suppressive effect of MIH is mediated by a cyclic nucleotide second messenger. A decrease in circulating MIH is associated with an increase in the hemolymphatic ecdysteroid titer during pre-molt. Nevertheless, it has long been hypothesized that a positive regulatory signal or stimulus is also involved in promoting ecdysteroidogenensis during premolt. Data reviewed here are consistent with the hypothesis that an intracellular Ca2+ signal provides that stimulus. Pharmacological agents that increase intracellular Ca2+ in Y-organs promote ecdysteroidogenesis, while agents that lower intracellular Ca2+ or disrupt Ca2+ signaling suppress ecdysteroidogenesis. Further, an increase in the hemolymphatic ecdysteroid titer after eyestalk ablation or during natural premolt is associated with an increase in intracellular free Ca2+ in Y-organ cells. Several lines of evidence suggest elevated intracellular calcium is linked to enhanced ecdysteroidogenesis through activation of Ca2+/calmodulin dependent cyclic nucleotide phosphodiesterase, thereby lowering intracellular cyclic nucleotide second messenger levels and promoting ecdysteroidogenesis. Results of transcriptomic studies show genes involved in Ca2+ signaling are well represented in Y-organs. Several recent studies have focused on Ca2+ transport proteins in Y-organs. Complementary DNAs encoding a plasma membrane Ca2+ ATPase (PMCA) and a sarcoplasmic/endoplasmic reticulum Ca2+ ATPase (SERCA) have been cloned from crab Y-organs. The relative abundance of PMCA and SERCA transcripts in Y-organs is elevated during premolt, a time when Ca2+ levels in Y-organs are likewise elevated. The results are consistent with the notion that these transport proteins act to maintain the Ca2+ gradient across the cell membrane and re-set the cell for future Ca2+ signals.

A Computer-Based Interactive Narrative and a Serious Game for Children With Asthma: Development and Content Validity Analysis.

BACKGROUND: Nonadherence to medications, failure to prevent exposure to asthma triggers, lack of knowledge about using medications, and fixed mindsets contribute to poor asthma control in children. Digital learning could provide a new strategy for improving health-related outcomes in children with asthma. OBJECTIVE: The aim of this study is to develop and design a digital educational program, titled Module of Inhaler and Asthma Triggers for Children (MIRACLE), for Indonesian children with asthma. The program comprises an interactive narrative and a serious game. It was proposed to increase the understanding of asthma self-management, instruct on proper inhaler techniques, improve asthma control, and promote a growth mindset for children with asthma. METHODS: Two phases of research were conducted to develop the program. In the first phase, a literature search and two rounds of the Delphi technique were conducted to obtain agreement from an expert panel regarding elements of asthma self-management and the design of interactive narratives and a serious game. The expert panel item statements were evaluated using the content validity index (CVI). In the second phase, the SERES framework, Norma Engaging Multimedia Design, and Psychological Theory of Growth Mindset were applied to create a storyline, learn objectives, and game challenges. RESULTS: In the first phase, 40 experts were invited to participate in Delphi round 1. Forty responses were collected to generate 38 item statements that consisted of part 1, elements of asthma self-management (25 items), and part 2, design of an interactive narrative and a serious game (13 items); 38 experts were involved in Delphi round 2. In total, 24 statements in part 1 and 13 items in part 2 had item-CVI values >0.80. The average CVI was 0.9, which was considered acceptable. Four narrative plots and five game sessions were developed during the second phase. Challenges with the scenario, scoring, and feedback on asthma difficulties were designed to promote a growth mindset for learners. CONCLUSIONS: We developed a culture-specific, computer-based asthma program containing an interactive narrative and a serious game to deliver asthma self-management and promote a growth mindset among Indonesian children.

The Crustacean Hyperglycemic Hormone Superfamily: Progress Made in the Past Decade.

Early studies recognizing the importance of the decapod eyestalk in the endocrine regulation of crustacean physiology-molting, metabolism, reproduction, osmotic balance, etc.-helped found the field of crustacean endocrinology. Characterization of putative factors in the eyestalk using distinct functional bioassays ultimately led to the discovery of a group of structurally related and functionally diverse neuropeptides, crustacean hyperglycemic hormone (CHH), molt-inhibiting hormone (MIH), gonad-inhibiting hormone (GIH) or vitellogenesis-inhibiting hormone (VIH), and mandibular organ-inhibiting hormone (MOIH). These peptides, along with the first insect member (ion transport peptide, ITP), constitute the original arthropod members of the crustacean hyperglycemic hormone (CHH) superfamily. The presence of genes encoding the CHH-superfamily peptides across representative ecdysozoan taxa has been established. The objective of this review is to, aside from providing a general framework, highlight the progress made during the past decade or so. The progress includes the widespread identification of the CHH-superfamily peptides, in particular in non-crustaceans, which has reshaped the phylogenetic profile of the superfamily. Novel functions have been attributed to some of the newly identified members, providing exceptional opportunities for understanding the structure-function relationships of these peptides. Functional studies are challenging, especially for the peptides of crustacean and insect species, where they are widely expressed in various tissues and usually pleiotropic. Progress has been made in deciphering the roles of CHH, ITP, and their alternatively spliced counterparts (CHH-L, ITP-L) in the regulation of metabolism and ionic/osmotic hemostasis under (eco)physiological, developmental, or pathological contexts, and of MIH in the stimulation of ovarian maturation, which implicates it as a regulator for coordinating growth (molt) and reproduction. In addition, experimental elucidation of the steric structure and structure-function relationships have given better understanding of the structural basis of the functional diversification and overlapping among these peptides. Finally, an important finding was the first-ever identification of the receptors for this superfamily of peptides, specifically the receptors for ITPs of the silkworm, which will surely give great impetus to the functional study of these peptides for years to come. Studies regarding recent progress are presented and synthesized, and prospective developments remarked upon.

Effects of Phyllanthus amarus extract on nonspecific immune responses, growth, and resistance to Vibrio alginolyticus in white shrimp Litopenaeus vannamei.

This study investigates the effects of Phyllanthus amarus extract (PAE) on immune responses, growth, and resistance to Vibrio alginolyticus in white shrimp (Litopenaeus vannamei). In vitro PAE treatment did not alter the cell viability of haemocytes and significantly enhanced immune parameters such as phenoloxidase (PO) activity, phagocytic activity, and superoxide anion (O2-) production. We conducted two feeding trials to examine the effects of PAE on the growth, disease resistance, and innate immune parameters of white shrimp. In the first in vivo trial, shrimps (4.01 ± 0.03 g) were fed a diet containing 0 g (control), 10 g (PAE10), 20 g (PAE20), or 40 g (PAE40) of PAE per kilogram of feed for 56 days. After the feeding period, the PAE20 group showed a significantly higher weight gain and specific growth rate than shrimp fed the control diet. Furthermore, after challenge with V. alginolyticus, shrimp fed a diet containing PAE showed significantly higher survival than those fed the control diet. The second in vivo trial (28 days) was performed to identify the mechanisms of enhanced immunity in PAE-fed shrimp. Shrimp fed the PAE20 diet generally had the highest total haemocyte count, PO activity, phagocytic activity, and O2- production, followed by the PAE40 and PAE10 groups. Thus, our results suggest that administration of 20 g of PAE per kilogram of feed can enhance immunity, growth, and resistance to V. alginolyticus in white shrimp.

Effects of three medicinal herbs Bidens pilosa, Lonicera japonica, and Cyathula officinalis on growth and non-specific immune responses of cobia (Rachycentron canadum).

This study investigates the effects of three medicinal herbal extracts, namely Bidens pilosa (BPE), Lonicera japonica (LJE), and Cyathula officinalis (COE), on nonspecific immune parameters of cobia (Rachycentron canadum) in vitro and in vivo. During in vitro tests, BPE treatment increased reactive oxygen species (ROS) production in a dose-dependent manner in primary head kidney leukocytes. Similarly, ROS production rates were enhanced by LJE (50 and 100 mg/ml) and COE (100 mg/ml). This suggests that these three herbal extracts possess immunostimulating properties. We then conducted two feeding trials to examine the effects of these three herbal extracts on growth and innate immune parameters of cobia, and sought an optimal dietary supplementation proportion required for activating the non-specific immune responses. In the first trial, we supplemented the diet with 1, 5, or 10% of the individual extracts. After a ten-week feeding trial, no negative impacts on weight gain, feed conversion rate, and survival rate were observed in fish offered experimental diets. Further, ROS production, phagocytic capacity of the head kidney leukocytes, and serum lysozyme activity were enhanced by differing degrees in fish fed the herbal extracts compared to fish in the control group. A similar albumin/globulin ratio was seen between each experimental group and the control group regardless of the type and dose of herbal extract used, indicating these medicinal herbal extracts are safe for cobia. We then performed a 30-day feeding trial with lower extract concentrations (1, 3, and 5% of the diet) to identify dose responses in cobia at various time points so that we could establish a cost-effective manner of administering the three extracts for cobia. All BPE fed fish had higher ROS production compared to the control group, while phagocytosis rate and index were simultaneously raised in only the BPE30 group (3% BPE). Immune parameters such as ROS production, phagocytic rate, and serum lysozyme activity were triggered when fish received 30 g LJE per kg of feed. However, ROS production only increased in the LJE10 group (1% LJE) on day 30 and was not enhanced in the LJE50 group (5% LJE). Additionally, although the phagocytic rate and phagocytic index were induced in the LJE50 group, serum lysozyme activity was not elevated in this group (LJE50) at any time point examined. ROS production was greatly improved in all COE fed groups, but only the COE30 group (3% COE) showed prolonged enhanced phagocytic rate over the 30-day feeding trial.

Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques.

BACKGROUND: The study compared the predictive outcomes of artificial neural network, support vector machine and random forest on the occurrence of anti-tuberculosis drug-induced hepatotoxicity. METHODS: The clinical and genomic data of patients treated with anti-tuberculosis drugs at Taipei Medical University-Wanfang Hospital were used as training sets, and those at Taipei Medical University-Shuang Ho Hospital served as test sets. Features were selected through a univariate risk factor analysis and literature evaluation. The accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve were calculated to compare the traditional, genomic, and combined models of the three techniques. RESULTS: Nine models were created with 7 clinical factors and 4 genotypes. Artificial neural network with clinical and genomic factors exhibited the best performance, with an accuracy of 88.67%, a sensitivity of 80%, and a specificity of 90.4% for the test set. The area under the receiver operating characteristic curve of this best model reached 0.894 for training set and 0.898 for test set, which was significantly better than 0.801 for training set and 0.728 for test set by support vector machine and 0.724 for training set and 0.718 for test set by random forest. CONCLUSIONS: Artificial neural network with clinical and genomic data can become a clinical useful tool in predicting anti-tuberculosis drug-induced hepatotoxicity. The machine learning technique can be an innovation to predict and prevent adverse drug reaction.

Variation of protein kinase C-α expression in eyestalk removal-activated ovaries in whiteleg shrimp, Litopenaeus vannamei.

The regulation of female reproduction in crustaceans is controlled by a variety of hormones. Previous studies of hormone-initiated cellular mechanisms controlling ovarian maturation focused mainly on those initiated by inhibitory hormones. In order to facilitate research on ovarian development, it is necessary to gain a better understanding of factors that promote ovarian growth on the cellular level. Here, we used eyestalk ablation to firstly induce a state of ovarian maturation in Litopenaeus vannamei. Gonadosomatic index, hemolymph vitellogenin (Vg) concentrations, and Vg gene transcript levels in the ovaries were significantly elevated at 1 and 2 weeks after eyestalk ablation (P < 0.05). Correspondingly, immunoblot analysis revealed a remarkable decrease in anti-PKC-α immunoreactivity in both cytosol and membrane fractions of ovarian tissue homogenates: it was strongly apparent in intact animals, but decreased with time after eyestalk ablation, showing a stronger tendency to do so in the membrane fraction than in the cytosol fraction. Considered overall, the data presented strongly suggest that PKC-α isoform plays a role in the regulation of ovarian growth in L. vannamei through a negative-based regulating mechanism.

Where and How Centenarians Die? The Role of Hospice Care.

The effect of hospice care on place of death among centenarians remained unexplored. Using data obtained from National Health Insurance Research Database (2002-2010), we compared the differences in place and cause of death between centenarians and noncentenarians. These data were stratified into centenarian (n = 2495) and noncentenarian (n = 820 563) death. Data in place and cause of death and hospice care interventions were retrieved. Poisson regression models were used to evaluate factors associated with the centenarians' place of death. Time series models were used to predict the number of centenarian deaths until 2025. Most (63.8%) of the centenarians died at their own homes, followed by 30.5% who died in hospital. Hospice home care was involved in only 0.3% of the centenarian deaths but in 1.8% of the noncentenarian deaths. The leading causes of death among centenarians were respiratory diseases (16.6%), circulatory diseases (15.2%), and pneumonia (14.8%). Among the centenarians, those who died of circulatory disease, old age, and respiratory diseases were more likely to die at their own homes. We forecasted the number of annual centenarian deaths to reach 800 in 2025. Therefore, an increase in the provision of advanced care planning and earlier home hospice care intervention may enable centenarians to die at their own residence.

Replacement Effects and Budget Impacts of Insurance Coverage for Sodium-Glucose Co-Transporter-2 Inhibitors on Oral Antidiabetic Drug Utilization.

BACKGROUND AND OBJECTIVES: A new oral antidiabetic drug class, sodium-glucose co-transporter-2 inhibitors (SGLT-2 inhibitors), has been covered by national health insurance in Taiwan since May 2016. This study estimated the impacts of insurance coverage for SGLT-2 inhibitors on the replacement effects of antidiabetic drug use and the overall budget for antidiabetic drugs in Taiwan. METHODS: Antidiabetic drugs were divided into nine categories based on the American Diabetes Association guidelines. We retrieved claims data from 2015 to 2017 for all patients diagnosed with diabetes mellitus from the National Health Insurance Research Database. An interrupted time series design and segmented regression were used to estimate the budget impact of insurance coverage for SGLT-2 inhibitors. Three scenarios were designed for the prescribing pattern for SGLT-2 inhibitors: (1) monotherapy, (2) metformin-based (m-based) drug prescriptions, and (3) metformin and sulfonylurea-based (m-s-based) drug prescriptions. RESULTS: From May 2016 to April 2017, the prescription rate for m-based SGLT-2 inhibitors increased from 0.43 to 3.50%, and the expenditure rate increased from 0.82 to 6.58%. We found that the prescription rates of m-based and m-s-based dipeptidyl peptidase-4 inhibitors (DPP-4 inhibitors) decreased by 6.23 and 11.51% following the initiation of insurance coverage for SGLT-2 inhibitors, respectively. Furthermore, there was a 5.95% increase in the overall budget impact of antidiabetic drugs 1 year following the initiation of insurance coverage for SGLT-2 inhibitors. CONCLUSIONS: Both the prescription rates and expenditure rates for SGLT-2 inhibitors have increased since they have been covered by national health insurance in Taiwan, which significantly reduced usage of DPP-4 inhibitors but caused the positive growth of overall antidiabetic drug expenditures.

Molecular cloning and characterization of a sarco/endoplasmic reticulum Ca2+ ATPase (SERCA) from Y-organs of the blue crab (Callinectes sapidus).

Existing data indicate that a Ca2+ signal stimulates ecdysteroid hormone production by crustacean molting glands (Y-organs). Ca2+ signaling is dependent on a tightly regulated Ca2+ gradient, with intracellular free Ca2+ maintained at a low basal level (typically sub-micromolar). This is achieved through the action of proteins intrinsic to the plasma membrane and the membranes of organelles. One such protein, the sarco/endoplasmic reticulum Ca2+ ATPase (SERCA), pumps Ca2+ from cytosol to the lumen of the endoplasmic reticulum. As a step toward understanding Ca2+-mediated regulation of ecdysteroidogenesis, we have begun investigating Ca2+ transport proteins in Y-organs. In studies reported here, we used a PCR-based strategy to clone from Y-organs of the blue crab (Callinectes sapidus) a cDNA encoding a putative SERCA protein. The cloned Cas-SERCA cDNA (3806 bp) includes a 3057-bp open reading frame that encodes a 1019-residue protein (Cas-SERCA). The conceptually translated protein has a predicted molecular mass of 111.42 × 103 and contains all signature domains of an authentic SERCA, including ten transmembrane domains and a phosphorylation site at aspartate 351. A homology model of Cas-SERCA closely resembles models of related SERCA proteins. Phylogenetic analysis shows Cas-SERCA clusters with SERCA proteins from other arthropods. An assessment of tissue distribution indicates the Cas-SERCA transcript is widely distributed across tissues. Studies using quantitative PCR showed Cas-SERCA transcript abundance increased significantly in Y-organs activated by eyestalk ablation, a pattern consistent with the hypothesis that Cas-SERCA functions to maintain Ca2+ homeostasis in Y-organs.

Current Impact and Application of Abuse-Deterrent Opioid Formulations in Clinical Practice.

BACKGROUND: Abuse-deterrent formulations (ADFs) represent one novel strategy for curbing the potential of opioid abuse. OBJECTIVE: We aim to compare and contrast the characteristics and applications of current abuse-deterrent opioid products in clinical practice. METHODS: Literature searches were conducted in databases (Pubmed Medline, International Pharmaceutical Abstracts, Google Scholar) and official reports. Relevant data were screened and organized into: 1) epidemiology of opioid abuse, 2) mitigation strategies for reducing opioid abuse, 3) development of ADFs, and 4) clinical experience with these formulations. RESULTS: Increasing trends of opioid abuse and misuse have been reported globally. There are 5 types of abuse-deterrent opioid products: physical chemical barrier, combined agonist/antagonist, sequestered aversive agent, prodrug, and novel delivery system. The advantages and disadvantages of the 5 options are discussed in this review. A total of 9 products with abuse-deterrent labels have been approved by the Food and Drug Administration (FDA). The rates of abuse, diversion, and overdose deaths of these new products are also discussed. A framework for collecting in-time data on the efficacy, benefit and risk ratio, and cost-effectiveness of these new products is suggested to facilitate their optimal use. LIMITATIONS: The present review did not utilize systematic review standards or meta-analytic techniques, given the large heterogeneity of data and outcomes reviewed. CONCLUSIONS: ADFs provide an option for inhibiting the abuse or misuse of oral opioid products by hindering extraction of the active ingredient, preventing alternative routes of administration, or causing aversion. Their relatively high costs, uncertain insurance policies, and limited data on pharmacoeconomics warrant collaborative monitoring and assessment by government agencies, pharmaceutical manufacturers, and data analysis services to define their therapeutic role in the future. KEY WORDS: Opioid abuse, abuse-deterrent formulations, ADF, post-marketing, FDA guidance, cost impact, abuse liking, physician attitude, generic abuse-deterrent formulation, clinical application.

Preliminary physician and pharmacist survey of the National Health Insurance PharmaCloud system in Taiwan.

BACKGROUND: The PharmaCloud system, a cloud-based medication system, was launched by the Taiwan National Health Insurance Administration (NHIA) in 2013 to integrate patients' medication lists among different medical institutions. The aim of the preliminary study was to evaluate satisfaction with this system among physicians and pharmacists at the early stage of system implementation. METHODS: A questionnaire was developed through a review of the literature and discussion in 6 focus groups to understand the level of satisfaction, attitudes, and intentions of physicians and pharmacists using the PharmaCloud system. It was then administered nationally in Taiwan in July to September 2015. Descriptive statistics and multiple regression were performed to identify variables influencing satisfaction and intention to use the system. RESULTS: In total, 895 pharmacist and 105 physician questionnaires were valid for analysis. The results showed that satisfaction with system quality warranted improvement. Positive attitudes toward medication reconciliation among physicians and pharmacists, which were significant predictors of the intention to use the system (ß= 0.223, p < 0.001). Most physicians and pharmacists agreed that obtaining signed patient consent was needed but preferred that it be conducted by the NHIA rather than by individual medical institutions (4.02 ± 1.19 vs. 3.49 ± 1.40, p < 0.01). CONCLUSIONS: The preliminary study results indicated a moderate satisfaction toward the PharmaCloud system. Hospital pharmacists had a high satisfaction rate, but neither are physicians and community pharmacists. Continuously improvement on system quality has been performing based on the results of this preliminary survey. Policies and standardization processes, including privacy protection, are still warranted further actions to make the Taiwan PharmaCloud system a convenient platform for medication reconciliation.

Involvement of second messengers in the signaling pathway of vitellogenesis-inhibiting hormone and their effects on vitellogenin mRNA expression in the whiteleg shrimp, Litopenaeus vannamei.

We incubated fragments of Litopenaeus vannamei ovary to investigate second messengers involved in the regulation of vitellogenin (vg) mRNA levels. The use of 100nM recombinant vitellogenesis-inhibiting hormone (VIH) (corresponding to recombinant L. vannamei sinus gland peptide-G: rLiv-SGP-G) significantly reduced vg mRNA expression in sub-adults after 8h incubation to less than 20% of the control. The concentration of intracellular cyclic guanosine monophosphate (cGMP) increased 3.2-fold relative to the control after 2h incubation with rLiv-SGP-G. However, it reached levels 18-fold relative to the control after 0.5h incubation with rLiv-SGP-G where 3-isobutyl-1-methylxanthine (a phosphodiesterase inhibitor) was also added. Moreover, vg mRNA expression was significantly reduced to less than 50% of the control after 24h incubation with 1µM A23187 (a calcium ionophore). Thus, rLiv-SGP-G and calcium ionophore reduced vg mRNA expression in in vitro-cultured ovary, and cGMP may be involved in the signaling pathway of VIH. Overall, the above results suggest that vg mRNA expression might be inhibited in vitro by increasing intracellular cGMP and Ca2+ in L. vannamei ovary.