The SLC36 transporter Pathetic is required for extreme dendrite growth in Drosophila sensory neurons.

Dendrites exhibit enormous diversity in form and can differ in size by several orders of magnitude even in a single animal. However, whether neurons with large dendrite arbors have specialized mechanisms to support their growth demands is unknown. To address this question, we conducted a genetic screen for mutations that differentially affected growth in neurons with different-sized dendrite arbors. From this screen, we identified a mutant that selectively affects dendrite growth in neurons with large dendrite arbors without affecting dendrite growth in neurons with small dendrite arbors or the animal overall. This mutant disrupts a putative amino acid transporter, Pathetic (Path), that localizes to the cell surface and endolysosomal compartments in neurons. Although Path is broadly expressed in neurons and nonneuronal cells, mutation of path impinges on nutrient responses and protein homeostasis specifically in neurons with large dendrite arbors but not in other cells. Altogether, our results demonstrate that specialized molecular mechanisms exist to support growth demands in neurons with large dendrite arbors and define Path as a founding member of this growth program.

Lozenges with probiotic strains enhance oral immune response and health.

OBJECTIVE: Probiotics participate in regulating oral microbiota and reducing the prevalence of oral diseases; however, clinical research on probiotics is insufficient. Therefore, in this study, we performed in vitro screening of potential oral protective probiotic strains and then evaluated the clinical efficacy of the selected strains on maintaining oral health. MATERIALS AND METHODS: Fifty healthy individuals were recruited and randomly assigned into the placebo group and probiotics group, which included three strains of probiotics, Lactobacillus salivarius subs. salicinius AP-32, Lactobacillus paracasei ET-66, and Lactobacillus plantarum LPL28. Each group was blindly administered placebo or probiotics for four weeks. RESULTS: Next-generation sequencing results showed that the oral microbiota of Lactobacillus salivarius in the oral cavity were significantly increased in subjects supplemented with mixed probiotic lozenges. The anti-bacterial activities of viable probiotics were observed within two weeks. Both IgA levels and Lactobacillus and Bifidobacterium abundances in the oral cavity were significantly increased in the experimental groups, along with a reduced formation of plaque. Most participants reported that their oral health conditions and intestinal symptoms had improved. CONCLUSIONS: Overall, our clinical study suggests that oral probiotic lozenges may enhance oral immunity, modulate oral microbiota, and improve oral health.

Probiotics and their Metabolites Reduce Oxidative Stress in Middle-Aged Mice.

Aging is an irreversible physiological degradation of living organisms. Accumulated oxidative stress and dysbiosis accelerate aging. Probiotics such as Lactobacillus and Bifidobacterium and their fermented metabolites (postbiotics) have been discovered to exhibit antioxidative activities that regulate oxidative stress and protect cells from oxidative damage. We screened selected Lactobacillus and Bifidobacterium strains and their postbiotics for potential antioxidative activity by using DPPH (2,2-Diphenyl-1-picrylhydrazyl) assay. Strains with their metabolites were selected for mixed formula in experiments involving aging mice. The aged groups presented higher oxidative stress in the brain, liver, heart, and kidney than did young mice. However, treatment with probiotic strains and their postbiotics elevated antioxidative levels, especially in the high-dose probiotics plus postbiotics group. Next-generation sequencing data revealed positive microbiota alterations of Lactobacillus and Bifidobacterium and Akkermansia in the gut. Lactobacillus johnsonii and Akkermansia muciniphila exhibited effective enlargement of relative abundance. Besides, high-dose probiotics and high-dose probiotics plus postbiotics showed significant elevation in serum SCFAs, especially in butyrate. In conclusion, the formula containing Bifidobacterium animalis subsp. infantis BLI-02, Bifidobacterium breve Bv889, Bifidobacterium bifidum VDD088, B. animalis subsp. lactis CP-9, and Lactobacillus plantarum PL-02 and their metabolites may benefit aged people's health.

Viable and Heat-Killed Probiotic Strains Improve Oral Immunity by Elevating the IgA Concentration in the Oral Mucosa.

Oral-nasal mucosal immunity plays a crucial role in protecting the body against bacterial and viral invasion. Safe probiotic products have been used to enhance human immunity and oral health. In this study, we verified the beneficial effects of mixed viable probiotic tablets, consisting of Lactobacillus salivarius subsp. salicinius AP-32, Bifidobacterium animalis subsp. lactis CP-9, and Lactobacillus paracasei ET-66, and heat-killed probiotic tablets, consisting of L. salivarius subsp. salicinius AP-32 and L. paracasei ET-66, on oral immunity among 45 healthy participants. Participants were randomly divided into viable probiotic, heat-killed probiotic, and placebo groups. The administration of treatment lasted for 4 weeks. Saliva samples were collected at Weeks 0, 2, 4, and 6, and Lactobacillus, Bifidobacterium and Streptococcus mutans populations and IgA concentration were measured. IgA concentrations, levels of TGF-beta and IL-10 in PBMCs cells were quantified by ELISA method. Results showed that salivary IgA levels were significantly increased on administration of both the viable (119.30 ± 12.63%, ***P < 0.001) and heat-killed (116.78 ± 12.28%, ***P < 0.001) probiotics for 4 weeks. Among three probiotic strains, AP-32 would effectively increase the levels of TGF-beta and IL-10 in PBMCs. The oral pathogen Streptococcus mutans was significantly reduced on viable probiotic tablet administration (49.60 ± 31.01%, ***P < 0.001). The in vitro antibacterial test confirmed that viable probiotics effectively limited the survival rate of oral pathogens. Thus, this clinical pilot study demonstrated that oral probiotic tablets both in viable form or heat-killed form could exert beneficial effects on oral immunity via IL-10, TGB-beta mediated IgA secretion. The effective dosage of viable probiotic content in the oral tablet was 109 CFUs/g and the heat-killed oral tablet was 1 × 1010 cells/g.

Coordinate control of terminal dendrite patterning and dynamics by the membrane protein Raw.

The directional flow of information in neurons depends on compartmentalization: dendrites receive inputs whereas axons transmit them. Axons and dendrites likewise contain structurally and functionally distinct subcompartments. Axon/dendrite compartmentalization can be attributed to neuronal polarization, but the developmental origin of subcompartments in axons and dendrites is less well understood. To identify the developmental bases for compartment-specific patterning in dendrites, we screened for mutations that affect discrete dendritic domains in Drosophila sensory neurons. From this screen, we identified mutations that affected distinct aspects of terminal dendrite development with little or no effect on major dendrite patterning. Mutation of one gene, raw, affected multiple aspects of terminal dendrite patterning, suggesting that Raw might coordinate multiple signaling pathways to shape terminal dendrite growth. Consistent with this notion, Raw localizes to branch-points and promotes dendrite stabilization together with the Tricornered (Trc) kinase via effects on cell adhesion. Raw independently influences terminal dendrite elongation through a mechanism that involves modulation of the cytoskeleton, and this pathway is likely to involve the RNA-binding protein Argonaute 1 (AGO1), as raw and AGO1 genetically interact to promote terminal dendrite growth but not adhesion. Thus, Raw defines a potential point of convergence in distinct pathways shaping terminal dendrite patterning.

PINK1-Parkin pathway activity is regulated by degradation of PINK1 in the mitochondrial matrix.

Loss-of-function mutations in PINK1, which encodes a mitochondrially targeted serine/threonine kinase, result in an early-onset heritable form of Parkinson's disease. Previous work has shown that PINK1 is constitutively degraded in healthy cells, but selectively accumulates on the surface of depolarized mitochondria, thereby initiating their autophagic degradation. Although PINK1 is known to be a cleavage target of several mitochondrial proteases, whether these proteases account for the constitutive degradation of PINK1 in healthy mitochondria remains unclear. To explore the mechanism by which PINK1 is degraded, we performed a screen for mitochondrial proteases that influence PINK1 abundance in the fruit fly Drosophila melanogaster. We found that genetic perturbations targeting the matrix-localized protease Lon caused dramatic accumulation of processed PINK1 species in several mitochondrial compartments, including the matrix. Knockdown of Lon did not decrease mitochondrial membrane potential or trigger activation of the mitochondrial unfolded protein stress response (UPRmt), indicating that PINK1 accumulation in Lon-deficient animals is not a secondary consequence of mitochondrial depolarization or the UPRmt. Moreover, the influence of Lon on PINK1 abundance was highly specific, as Lon inactivation had little or no effect on the abundance of other mitochondrial proteins. Further studies indicated that the processed forms of PINK1 that accumulate upon Lon inactivation are capable of activating the PINK1-Parkin pathway in vivo. Our findings thus suggest that Lon plays an essential role in regulating the PINK1-Parkin pathway by promoting the degradation of PINK1 in the matrix of healthy mitochondria.

Privacy preserving data anonymization of spontaneous ADE reporting system dataset.

BACKGROUND: To facilitate long-term safety surveillance of marketing drugs, many spontaneously reporting systems (SRSs) of ADR events have been established world-wide. Since the data collected by SRSs contain sensitive personal health information that should be protected to prevent the identification of individuals, it procures the issue of privacy preserving data publishing (PPDP), that is, how to sanitize (anonymize) raw data before publishing. Although much work has been done on PPDP, very few studies have focused on protecting privacy of SRS data and none of the anonymization methods is favorable for SRS datasets, due to which contain some characteristics such as rare events, multiple individual records, and multi-valued sensitive attributes. METHODS: We propose a new privacy model called MS(k, θ (*) )-bounding for protecting published spontaneous ADE reporting data from privacy attacks. Our model has the flexibility of varying privacy thresholds, i.e., θ (*) , for different sensitive values and takes the characteristics of SRS data into consideration. We also propose an anonymization algorithm for sanitizing the raw data to meet the requirements specified through the proposed model. Our algorithm adopts a greedy-based clustering strategy to group the records into clusters, conforming to an innovative anonymization metric aiming to minimize the privacy risk as well as maintain the data utility for ADR detection. Empirical study was conducted using FAERS dataset from 2004Q1 to 2011Q4. We compared our model with four prevailing methods, including k-anonymity, (X, Y)-anonymity, Multi-sensitive l-diversity, and (α, k)-anonymity, evaluated via two measures, Danger Ratio (DR) and Information Loss (IL), and considered three different scenarios of threshold setting for θ (*) , including uniform setting, level-wise setting and frequency-based setting. We also conducted experiments to inspect the impact of anonymized data on the strengths of discovered ADR signals. RESULTS: With all three different threshold settings for sensitive value, our method can successively prevent the disclosure of sensitive values (nearly all observed DRs are zeros) without sacrificing too much of data utility. With non-uniform threshold setting, level-wise or frequency-based, our MS(k, θ (*))-bounding exhibits the best data utility and the least privacy risk among all the models. The experiments conducted on selected ADR signals from MedWatch show that only very small difference on signal strength (PRR or ROR) were observed. The results show that our method can effectively prevent the disclosure of patient sensitive information without sacrificing data utility for ADR signal detection. CONCLUSIONS: We propose a new privacy model for protecting SRS data that possess some characteristics overlooked by contemporary models and an anonymization algorithm to sanitize SRS data in accordance with the proposed model. Empirical evaluation on the real SRS dataset, i.e., FAERS, shows that our method can effectively solve the privacy problem in SRS data without influencing the ADR signal strength.

Rough-set-based ADR signaling from spontaneous reporting data with missing values.

Spontaneous reporting systems of adverse drug events have been widely established in many countries to collect as could as possible all adverse drug events to facilitate the detection of suspected ADR signals via some statistical or data mining methods. Unfortunately, due to privacy concern or other reasons, the reporters sometimes may omit consciously some attributes, causing many missing values existing in the reporting database. Most of research work on ADR detection or methods applied in practice simply adopted listwise deletion to eliminate all data with missing values. Very little work has noticed the possibility and examined the effect of including the missing data in the process of ADR detection. This paper represents our endeavor towards the exploration of this question. We aim at inspecting the feasibility of applying rough set theory to the ADR detection problem. Based on the concept of utilizing characteristic set based approximation to measure the strength of ADR signals, we propose twelve different rough set based measuring methods and show only six of them are feasible for the purpose. Experimental results conducted on the FARES database show that our rough-set-based approach exhibits similar capability in timeline warning of suspicious ADR signals as traditional method with missing deletion, and sometimes can yield noteworthy measures earlier than the traditional method.

A GA-based approach to hide sensitive high utility itemsets.

A GA-based privacy preserving utility mining method is proposed to find appropriate transactions to be inserted into the database for hiding sensitive high utility itemsets. It maintains the low information loss while providing information to the data demanders and protects the high-risk information in the database. A flexible evaluation function with three factors is designed in the proposed approach to evaluate whether the processed transactions are required to be inserted. Three different weights are, respectively, assigned to the three factors according to users. Moreover, the downward closure property and the prelarge concept are adopted in the proposed approach to reduce the cost of rescanning database, thus speeding up the evaluation process of chromosomes.

Stacking Ensemble of Disproportionality Indicators for Adverse Vaccine Reactions Detection-An Empirical Study on Predicting Adverse Reactions of COVID-19 Vaccines.

Vaccine safety is a critical issue for public health, which has recently become more crucial than ever since COVID-19 started to spread worldwide in 2020. Many COVID-19 vaccines have been developed and used without following the traditional three clinical trial stages. Instead, most COVID-19 vaccines were approved through emergency use approval (EUA) within one year, significantly raising the risk of rare and severe adverse events. Reporting systems like the Vaccine Adverse Event Reporting System (VAERS) have been established worldwide to detect unknown and severe adverse reactions as early as possible. Although experts and researchers have been working hard to find ways to detect adverse vaccine event (AVE) signals from VAERS data, most of the contemporary methods are statistical methods based on measuring the disproportionality between vaccine-induced events and non-vaccine-induced events. This paper proposes a novel ensemble AVE detection method, which adopts a stacking ensemble of various disproportionality indicators, fusing dual-scale contingency values measured in single and cumulative yearly duration, and embraces the concept of feature concatenation. Experiments conducted on US VAERS data to predict AVE caused by COVID-19 vaccines show that our proposed method is effective. We observed that: (1) Stacking ensemble of various disproportionality indicators is superior to any single disproportionality indicator and voting ensemble method; (2) Fusing dual-scale contingency values and feature concatenation brings synergy to our proposed stacking ensemble AVE detection. Compared to the best disproportionality metric in this study, our top-performing ensemble version exhibited a 34% improvement in accuracy, 71% in precision, 29% in recall, and 77% in F-measure, with a slight decrease (8%) in specificity.