Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes.

The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

Challenges in benchmarking metagenomic profilers.

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.

Latent subgroups with distinct patterns of factors associated with self-rated successful aging among 1,510 community-dwelling Americans: potential role of wisdom as an implicit promoter.

OBJECTIVES: To investigate whether latent subgroups with distinct patterns of factors associated with self-rated successful aging can be identified in community-dwelling adults, and how such patterns obtained from analysis of quantitative data are associated with lay perspectives on successful aging obtained from qualitative responses. METHODS: Cross-sectional data were collected from 1,510 community-dwelling Americans aged 21-99 years. Latent class regression was used to identify subgroups that explained the associations of self-rated successful aging with measures of physical, cognitive, and mental health as well as psychological measures related to resilience and wisdom. Natural language processing was used to extract important themes from qualitative responses to open-ended questions, including the participants' definitions of successful aging. RESULTS: Two latent subgroups were identified, and their main difference was that the wisdom scale was positively associated with self-rated successful aging in only one subgroup. This subgroup had significantly lower self-rated successful aging and worse scores for all health and psychological measures. In the subgroup's qualitative responses, the theme of wisdom was only mentioned by 10.6%; this proportion was not statistically different from the other subgroup, for which the wisdom scale was not statistically associated with the self-rated successful aging. CONCLUSION: Our results showed heterogeneous patterns in the factors underpinning successful aging even in community-dwelling adults. We found the existence of a latent subgroup with lower self-rated successful aging as well as worse health and psychological scores, and we suggest a potential role of wisdom in promoting successful aging for this subgroup, even though individuals may not explicitly recognize wisdom as important for successful aging.

Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data.

Feature selection is indispensable in microbiome data analysis, but it can be particularly challenging as microbiome data sets are high dimensional, underdetermined, sparse and compositional. Great efforts have recently been made on developing new methods for feature selection that handle the above data characteristics, but almost all methods were evaluated based on performance of model predictions. However, little attention has been paid to address a fundamental question: how appropriate are those evaluation criteria? Most feature selection methods often control the model fit, but the ability to identify meaningful subsets of features cannot be evaluated simply based on the prediction accuracy. If tiny changes to the data would lead to large changes in the chosen feature subset, then many selected features are likely to be a data artifact rather than real biological signal. This crucial need of identifying relevant and reproducible features motivated the reproducibility evaluation criterion such as Stability, which quantifies how robust a method is to perturbations in the data. In our paper, we compare the performance of popular model prediction metrics (MSE or AUC) with proposed reproducibility criterion Stability in evaluating four widely used feature selection methods in both simulations and experimental microbiome applications with continuous or binary outcomes. We conclude that Stability is a preferred feature selection criterion over model prediction metrics because it better quantifies the reproducibility of the feature selection method.

Rates of Cognitive and Functional Impairments in Older Adults Residing in a Continuing Care Senior Housing Community.

OBJECTIVE: The current cross-sectional study examined cognition and performance-based functional abilities in a continuing care senior housing community (CCSHC) that is comparable to other CCSHCs in the US with respect to residents' demographic characteristics. METHOD: Participants were 110 older adult residents of the independent living unit. We assessed sociodemographics, mental health, neurocognitive functioning, and functional capacity. RESULTS: Compared to normative samples, participants performed at or above expectations in terms of premorbid functioning, attention span and working memory, processing speed, timed set-shifting, inhibitory control, and confrontation naming. They performed below expectation in verbal fluency and verbal and visual learning and memory, with impairment rates [31.4% (>1 SD below the mean) and 18.49% (>1.5 SD below the mean)] well above the general population (16% and 7%, respectively). Within the cognitive test battery, two tests of delayed memory were most predictive of a global deficit score. Most cognitive test scores correlated with performance-based functional capacity. CONCLUSIONS: Overall, results suggest that a subset of older adults in the independent living sector of CCSHCs are cognitively and functionally impaired and are at risk for future dementia. Results also argue for the inclusion of memory tests in abbreviated screening batteries in this population. We suggest that CCSHCs implement regular cognitive screening procedures to identify and triage those older adults who could benefit from interventions and, potentially, a transition to a higher level of care.

Prediction of Loneliness in Older Adults Using Natural Language Processing: Exploring Sex Differences in Speech.

OBJECTIVE: The growing pandemic of loneliness has great relevance to aging populations, though assessments are limited by self-report approaches. This paper explores the use of artificial intelligence (AI) technology to evaluate interviews on loneliness, notably, employing natural language processing (NLP) to quantify sentiment and features that indicate loneliness in transcribed speech text of older adults. DESIGN: Participants completed semi-structured qualitative interviews regarding the experience of loneliness and a quantitative self-report scale (University of California Los Angeles or UCLA Loneliness scale) to assess loneliness. Lonely and non-lonely participants (based on qualitative and quantitative assessments) were compared. SETTING: Independent living sector of a senior housing community in San Diego County. PARTICIPANTS: Eighty English-speaking older adults with age range 66-94 (mean 83 years). MEASUREMENTS: Interviews were audiotaped and manually transcribed. Transcripts were examined using NLP approaches to quantify sentiment and expressed emotions. RESULTS: Lonely individuals (by qualitative assessments) had longer responses with greater expression of sadness to direct questions about loneliness. Women were more likely to endorse feeling lonely during the qualitative interview. Men used more fearful and joyful words in their responses. Using linguistic features, machine learning models could predict qualitative loneliness with 94% precision (sensitivity = 0.90, specificity = 1.00) and quantitative loneliness with 76% precision (sensitivity = 0.57, specificity = 0.89). CONCLUSIONS: AI (e.g., NLP and machine learning approaches) can provide unique insights into how linguistic features of transcribed speech data may reflect loneliness. Eventually linguistic features could be used to assess loneliness of individuals, despite limitations of commercially developed natural language understanding programs.

Phytochemicals from the flowers of Prunus persica (L.) Batsch: Anti-adipogenic effect of mandelamide on 3T3-L1 preadipocytes.

Flowers of Prunus persica (L.) Batsch (Rosaceae), known as peach blossoms, have been reported to exert anti-obesity effects by improving hepatic lipid metabolism in obese mice. However, little is known regarding the anti-adipogenic effects of the phenolic compounds isolated from P. persica flowers. This study investigated the inhibitory effects of compounds extracted from P. persica flowers (PPF) on adipogenesis in 3T3-L1 murine preadipocytes using adipogenic differentiation assays. Additionally, we compared the anti-adipogenic effects of the phenolic compounds isolated from PPF, such as prunasin amide (1), amygdalin amide (2), prunasin acid (3), mandelamide (4), methyl caffeate (5), ferulic acid (6), chlorogenic acid (7), benzyl α-l-xylpyranosyl-(1 â†’ 6)-ß-d-glucopyranoside (8), prunin (9), naringenin (10), nicotiflorin (11), astragalin (12), afzelin (13), and uridine (14), on adipogenesis in 3T3-L1 murine preadipocytes. PPF and compounds 4-7 and 10 significantly inhibited adipogenesis. Among them, mandelamide (4) exhibited the maximum inhibitory activity with an IC50 of 36.04 ± 1.82 µM. Additionally, mandelamide downregulated the expression of key adipogenic markers, such as extracellular signal-regulated kinase, c-Jun-N-terminal kinase, P38, CCAAT/enhancer-binding protein α, CCAAT/enhancer-binding protein ß, peroxisome proliferator activated receptor γ, and glucocorticoid receptor. These results indicate that mandelamide is an active ingredient of PPF possessing anti-obesity properties.

Qualitative study of loneliness in a senior housing community: the importance of wisdom and other coping strategies.

OBJECTIVE: Older adults are at a high risk for loneliness, which impacts their health, well-being, and longevity. While related to social isolation, loneliness is a distinct, internally experienced, distressing feeling. The present qualitative study sought to identify characteristics of loneliness in older adults living independently within a senior housing community, which is typically designed to reduce social isolation. METHOD: Semi-structured qualitative interviews regarding the experience of loneliness, risk factors, and ways to combat it were conducted with 30 older adults, ages 65-92 years. The interviews were audiotaped, transcribed, and coded using a grounded theory analytic approach based on coding, consensus, co-occurrence, and comparison. RESULTS: Three main themes with multiple subthemes are described: (A) Risk and Protective factors for loneliness: age-associated losses, lack of social skills or abilities, and protective personality traits; (B) Experience of loneliness: Sadness and lack of meaning as well as Lack of motivation; and (C) Coping strategies to prevent or overcome loneliness: acceptance of aging, compassion, seeking companionship, and environment enables socialization. DISCUSSION: Despite living within a communal setting designed to reduce social isolation, many older adults described feeling lonely in stark negative terms, attributing it to aging-associated losses or lack of social skills and abilities. However, interviewees also reported positive personal qualities and actions to prevent or cope with loneliness, several of which mirrored specific components of wisdom. The results support the reported inverse relationship between loneliness and wisdom and suggest a potential role for wisdom-enhancing interventions to reduce and prevent loneliness in older populations.

Association between Advanced Lung Inflammation Index and 30-Day Mortality in Patients with Acute Respiratory Distress Syndrome.

Background and objectives: The advanced lung inflammation index (ALI) was developed to assess the degree of systemic inflammation and has an association with prognosis in patients with lung malignancy. The prognostic value of ALI has not yet been evaluated in patients with acute respiratory distress syndrome (ARDS). Materials and Methods: Between January 2014 and May 2018, patients with ARDS in the medical intensive care unit (ICU) were reviewed retrospectively. The ALI value was calculated as the (body mass index × serum albumin level)/neutrophil-lymphocyte ratio. The cut-off value for distinguishing low from high ALI was defined according to receiver-operating characteristic curve analysis. Results: A total of 164 patients were analyzed. Their median age was 73 years, and 73% was male. The main cause of ARDS was pneumonia (95.7%, 157/164). ICU and in-hospital mortality rates were 59.8% (98/164) and 64% (105/164), respectively. The 30 day mortality was 60.9% (100/164). The median ALI value in non-survivors was lower than that in survivors at 30 day (3.81 vs. 7.39, p = 0.005). In multivariate analysis, low ALI value (≤5.38) was associated with increased 30 day mortality (odds ratio, 2.944, confidence interval 1.178-7.355, p = 0.021). Conclusions: A low ALI value was associated with increased 30 day mortality in patients with ARDS.

Ginger and 6-shogaol protect intestinal tight junction and enteric dopaminergic neurons against 1-methyl-4-phenyl 1,2,3,6-tetrahydropyridine in mice.

Objective: Ginger and its compound, 6-shogaol, have been known for improving gastrointestinal (GI) function and reducing inflammatory responses in GI tract. Recently, the treatment of GI dysfunction has been recognized as an important part of the management of neurodegenerative diseases, especially for Parkinson's disease (PD). In this study, we investigated whether ginger and 6-shogaol attenuate disruptions induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) on the intestinal barrier and the enteric dopaminergic neurons.Methods: C57BL/6J mice received MPTP (30 mg/kg) for 5 days to induce GI alterations. Ginger (30, 100, 300 mg/kg) and 6-shogaol (10 mg/kg) were treated by gavage feeding for 15 days including the period of MPTP injection.Results: Ginger and 6-shogaol protected intestinal tight junction proteins disrupted by MPTP in mouse colon. In addition, ginger and 6-shogaol suppressed the increase of inducible nitric oxide synthase, cyclooxygenase-2, TNF-α and IL-1ß activated by macrophage. Moreover, ginger and 6-shogaol suppressed the MPTP-induced enteric dopaminergic neuronal damage via increasing the cell survival signaling pathway.Conclusion: These results indicate that ginger and 6-shogaol restore the disruption of intestinal integrity and enteric dopaminergic neurons in an MPTP-injected mouse PD model by inhibiting the processes of inflammation and apoptosis, suggesting that they may attenuate the GI dysfunction in PD patients.

Beyond artificial intelligence: exploring artificial wisdom.

BACKGROUND: The ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term "intelligence" does not best represent the technological needs of advancing society, because it is "wisdom", rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW). METHODS: We examine the constructs of human intelligence and human wisdom in terms of their basic components, neurobiology, and relationship to aging, based on published empirical literature. We review the development of AI as inspired and driven by the model of human intelligence, and consider possible governing principles for AW that would enable humans to develop computers which can operationally utilize wise principles and result in wise acts. We review relevant examples of current efforts to develop such wise technologies. RESULTS: AW systems will be based on developmental models of the neurobiology of human wisdom. These AW systems need to be able to a) learn from experience and self-correct; b) exhibit compassionate, unbiased, and ethical behaviors; and c) discern human emotions and help the human users to regulate their emotions and make wise decisions. CONCLUSIONS: A close collaboration among computer scientists, neuroscientists, mental health experts, and ethicists is necessary for developing AW technologies, which will emulate the qualities of wise humans and thus serve the greatest benefit to humanity. Just as human intelligence and AI have helped further the understanding and usefulness of each other, human wisdom and AW can aid in promoting each other's growth.

Resequencing Study Confirms That Host Defense and Cell Senescence Gene Variants Contribute to the Risk of Idiopathic Pulmonary Fibrosis.

Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 × 10-295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence.

Gastroprotective Effects of Inulae Flos on HCl/Ethanol-Induced Gastric Ulcers in Rats.

Inulae Flos, the flower of Inula britannica L., is used as a dietary supplement, beverage, and medicine in East Asia. In this study, we evaluated the gastroprotective effects of Inulae Flos extract (IFE) against gastric mucosal lesions induced by hydrochloric acid (HCl)/ethanol in rats and explored its potential mechanisms by measuring antioxidant enzyme activity, mucus secretion, and prostaglandin E2 (PGE2) levels. Pretreatment with IFE at doses of 100 and 300 mg/kg significantly inhibited gastric lesions in HCl/ethanol-treated rats. IFE increased the activities of superoxide dismutase and catalase and the levels of glutathione and PGE2 in gastric tissues. The administration of IFE also significantly increased the gastric wall mucus contents in HCl/ethanol-induced gastric lesions. These findings suggest that IFE has gastroprotective effects against HCl/ethanol-induced gastric lesions and exerts these effects through increased antioxidant levels and gastric mucus secretion. Inulae Flos may be a promising agent for the prevention and treatment of gastritis and gastric ulcers.

Longitudinal Bone Growth Stimulating Effect of Allium macrostemon in Adolescent Female Rats.

Allium macrostemon (AM) may affect bone growth by regulating bone formation and resorption. To examine the effect of AM on bone growth, 48 rats were divided into four administration groups in which either distilled water, AM (100 and 300 mg/kg), or recombinant human growth hormone (rhGH; 20 µg/kg) was administered for 10 days. On day 9, all animals were intraperitoneally injected with tetracycline hydrochloride (20 mg/kg), and 48 h after the injection, the rats were sacrificed. Their tibial sections were photographed to measure bone growth. Antigen-specific immunohistochemistry was performed to detect insulin-like growth factor-1 (IGF-1) and bone morphogenetic protein-2 (BMP-2). The food intake of the AM 100 mg/kg group was higher; however, the food intake of the AM 300 mg/kg group was less than that of the control group. The rhGH and AM 100 mg/kg groups showed greater rates of bone growth (359.0 ± 23.7 and 373.1 ± 28.0 µm/day, respectively) compared with the control group. IGF-1 and BMP-2 in the AM and rhGH groups were highly expressed. Indigestion at higher doses of AM led to nonsignificant bone growth in spite of increased IGF-1 and BMP-2 expression. Therefore, a suitable amount of AM could increase bone growth.

Study of Independent Living Residents of a Continuing Care Senior Housing Community: Sociodemographic and Clinical Associations of Cognitive, Physical, and Mental Health.

OBJECTIVE: To examine associations of sociodemographic and clinical factors with cognitive, physical, and mental health among independent living older adults in a continuing care senior housing community (CCSHC). METHODS: This was a cross-sectional study at the independent living sector of a CCSHC in San Diego County, California. Participants included English-speaking adults aged 65-95 years, of which two-thirds were women. Of the 112 subjects recruited, 104 completed basic study assessments. The authors computed composite measures of cognitive, physical, and mental health. The authors also assessed relevant clinical correlates including psychosocial factors such as resilience, loneliness, wisdom, and social support. RESULTS: The CCSHC residents were similar to a randomly selected community-based sample of older adults on most standardized clinical measures. In the CCSHC, physical health correlated with both cognitive function and mental health, but there was no significant correlation between cognitive and mental health. Cognitive function was significantly associated with physical mobility, satisfaction with life, and wisdom, whereas physical health was associated with age, self-rated physical functioning, mental well-being, and resilience. Mental health was significantly associated with income, optimism, self-compassion, loneliness, and sleep disturbances. CONCLUSION: Different psychosocial factors are significantly associated with cognitive, physical, and mental health. Longitudinal studies of diverse samples of older adults are necessary to determine risk factors and protective factors for specific domains of health. With rapidly growing numbers of older adults who require healthcare as well as supportive housing, CCSHCs will become increasingly important sites for studying and promoting the health of older adults.

Artificial Intelligence for Mental Health and Mental Illnesses: an Overview.

PURPOSE OF REVIEW: Artificial intelligence (AI) technology holds both great promise to transform mental healthcare and potential pitfalls. This article provides an overview of AI and current applications in healthcare, a review of recent original research on AI specific to mental health, and a discussion of how AI can supplement clinical practice while considering its current limitations, areas needing additional research, and ethical implications regarding AI technology. RECENT FINDINGS: We reviewed 28 studies of AI and mental health that used electronic health records (EHRs), mood rating scales, brain imaging data, novel monitoring systems (e.g., smartphone, video), and social media platforms to predict, classify, or subgroup mental health illnesses including depression, schizophrenia or other psychiatric illnesses, and suicide ideation and attempts. Collectively, these studies revealed high accuracies and provided excellent examples of AI's potential in mental healthcare, but most should be considered early proof-of-concept works demonstrating the potential of using machine learning (ML) algorithms to address mental health questions, and which types of algorithms yield the best performance. As AI techniques continue to be refined and improved, it will be possible to help mental health practitioners re-define mental illnesses more objectively than currently done in the DSM-5, identify these illnesses at an earlier or prodromal stage when interventions may be more effective, and personalize treatments based on an individual's unique characteristics. However, caution is necessary in order to avoid over-interpreting preliminary results, and more work is required to bridge the gap between AI in mental health research and clinical care.

High prevalence and adverse health effects of loneliness in community-dwelling adults across the lifespan: role of wisdom as a protective factor.

OBJECTIVES: This study of loneliness across adult lifespan examined its associations with sociodemographics, mental health (positive and negative psychological states and traits), subjective cognitive complaints, and physical functioning. DESIGN: Analysis of cross-sectional data. PARTICIPANTS: 340 community-dwelling adults in San Diego, California, mean age 62 (SD = 18) years, range 27-101 years, who participated in three community-based studies. MEASUREMENTS: Loneliness measures included UCLA Loneliness Scale Version 3 (UCLA-3), 4-item Patient-Reported Outcomes Measurement Information System (PROMIS) Social Isolation Scale, and a single-item measure from the Center for Epidemiologic Studies Depression (CESD) scale. Other measures included the San Diego Wisdom Scale (SD-WISE) and Medical Outcomes Survey- Short form 36. RESULTS: Seventy-six percent of subjects had moderate-high levels of loneliness on UCLA-3, using standardized cut-points. Loneliness was correlated with worse mental health and inversely with positive psychological states/traits. Even moderate severity of loneliness was associated with worse mental and physical functioning. Loneliness severity and age had a complex relationship, with increased loneliness in the late-20s, mid-50s, and late-80s. There were no sex differences in loneliness prevalence, severity, and age relationships. The best-fit multiple regression model accounted for 45% of the variance in UCLA-3 scores, and three factors emerged with small-medium effect sizes: wisdom, living alone and mental well-being. CONCLUSIONS: The alarmingly high prevalence of loneliness and its association with worse health-related measures underscore major challenges for society. The non-linear age-loneliness severity relationship deserves further study. The strong negative association of wisdom with loneliness highlights the potentially critical role of wisdom as a target for psychosocial/behavioral interventions to reduce loneliness. Building a wiser society may help us develop a more connected, less lonely, and happier society.

Effects of Eleutherococcus Extract Mixture on Endochondral Bone Formation in Rats.

Eleutherococcus extract mixture (EEM) is an herbal mixture of dried stem of Eleutherococcus sessiliflorus and germinated barley, which has been highly effective, in previous screening and among the traditional medicines to tonify innate qi and acquired qi, respectively. In this study, we investigate the effects of EEM on endochondral bone formation. Female adolescent rats were given EEM, growth hormone or vehicle for 10 days. Tetracycline was intraperitoneally injected to light the fluorescent band 72 h before sacrifice to determine endochondral bone formation. In order to evaluate endocrine or paracrine/autocrine mechanisms, expressions of insulin-like growth factor 1 (IGF1), insulin-like growth factor binding protein 3 (IGFBP3), or bone morphogenetic protein 2 (BMP2) were evaluated after EEM administration in liver or growth plate (GP). EEM oral administration significantly increased endochondral bone formation and proliferative and hypertrophic zonal heights of tibial GP. EEM also upregulated hepatic IGF1 and IGFBP3 mRNA expressions, and IGF1 and BMP2 expressions in GP. Taken together, EEM increases endochondral bone formation through stimulating proliferation and hypertrophy with upregulation of hepatic IGF1 and IGFBP3 expressions. Considering immunohistochemical studies, the effect of EEM may be due to increased local IGF1 and BMP2 expression in GP, which may be considered growth hormone (GH)-dependent endocrine and autocrine/paracrine pathways.

How Solid-Electrolyte Interphase Forms in Aqueous Electrolytes.

Solid-electrolyte interphase (SEI) is the key component that enables all advanced electrochemical devices, the best representative of which is Li-ion battery (LIB). It kinetically stabilizes electrolytes at potentials far beyond their thermodynamic stability limits, so that cell reactions could proceed reversibly. Its ad hoc chemistry and formation mechanism has been a topic under intensive investigation since the first commercialization of LIB 25 years ago. Traditionally SEI can only be formed in nonaqueous electrolytes. However, recent efforts successfully transplanted this concept into aqueous media, leading to significant expansion in the electrochemical stability window of aqueous electrolytes from 1.23 V to beyond 4.0 V. This not only made it possible to construct a series of high voltage/energy density aqueous LIBs with unprecedented safety, but also brought high flexibility and even "open configurations" that have been hitherto unavailable for any LIB chemistries. While this new class of aqueous electrolytes has been successfully demonstrated to support diversified battery chemistries, the chemistry and formation mechanism of the key component, an aqueous SEI, has remained virtually unknown. In this work, combining various spectroscopic, electrochemical and computational techniques, we rigorously examined this new interphase, and comprehensively characterized its chemical composition, microstructure and stability in battery environment. A dynamic picture obtained reveals how a dense and protective interphase forms on anode surface under competitive decompositions of salt anion, dissolved ambient gases and water molecule. By establishing basic laws governing the successful formation of an aqueous SEI, the in-depth understanding presented in this work will assist the efforts in tailor-designing better interphases that enable more energetic chemistries operating farther away from equilibria in aqueous media.

The Korean herbal formulation Yukmijihwangtang stimulates longitudinal bone growth in animal models.

BACKGROUND: Yukmijihwangtang (YJT) is a traditional Korean medicine that has been used to treat kidney-yin deficiency symptoms such as dizziness and tinnitus. In addition, because it is also thought to nourish kidney-yin, it has been used to treat short stature from congenital deficiency. This study evaluated the effects of YJT on longitudinal bone growth in rats. METHODS: Female adolescent rats were randomly assigned to groups that received distilled water (per os [p.o.] twice a day; control), recombinant human growth hormone (rhGH; 20 µg/kg, subcutaneous [s.c.] once a day), or two different doses of YJT (100 or 300 mg/kg, p.o. twice a day). In each group, treatment was maintained for 4 days. Rats were injected intraperitoneally with 5-bromo-2'-deoxyuridine (BrdU; 50 mg/kg) to label proliferating chondrocytes on days 2 - 4. Tetracycline hydrochloride (20 mg/kg) was injected intraperitoneally to form fluorescent bands on the growth plates on day 3 for measuring the longitudinal bone growth rate. Expression of insulin-like growth factor-1 (IGF-1) and bone morphogenetic protein-2 (BMP-2) in the growth plate was identified using immunohistochemistry. RESULTS: There was a significant increase in the rate of bone growth in the 300 mg/kg YJT group (523.8 ± 23.7 µm/day; P < 0.05) compared to the control group (498.0 ± 23.8 µm/day), while the 100 mg/kg YJT group exhibited a non-significant increase. The number of BrdU-positive cells in the chondrocytes of the rhGH-treated group exhibited a significant increase (103.8 ± 34.2 cells/mm2) compared to that of the control group (70.3 ± 19.7 cells/mm2), while the 300 mg/kg YJT group had a non-significant increase. Additionally, IGF-1 and BMP-2 were highly expressed in the growth plate in the 300 mg/kg YJT and rhGH groups. CONCLUSIONS: YJT increased the longitudinal bone growth rate by stimulating chondrocyte proliferation with increasing increments of local IGF-1 and BMP-2 expression. Based on these findings, YJT may be a therapeutic candidate for the treatment of growth retardation during adolescence.