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Mitochondria are promising drug target for cancer treatment. We previously demonstrated that a bi-gold compound BGC2a was more potent than the mono-gold drug auranofin in suppressing cancer cells due to increased gold atom number that led to higher drug accumulation in and thereby inhibition of mitochondria. To exploit the potential of this new strategy, we further designed and synthesized a series of bi-gold mitocans, the compounds targeting mitochondria. The results showed that most of the newly synthesized mitocans exhibited obviously lower IC50 than auranofin, an old drug that is repurposed in clinical trials for cancer treatment. The best mitocan C3P4 was nearly 2-fold more potent than BGC2a in human non-small cell lung cancer A549 cells and mantle cell lymphoma Jeko-1 cells, exhibiting substantial colony formation-suppressing and tumor-suppressing effects in A549 cells xenograft model. C3P4 induced apoptosis in a dose-dependent manner and arrested cell cycle at G0/G1 phase. The mechanistic study showed that C3P4 significantly increased the global reactive oxygen species and mitochondrial superoxide level, and reduced the mitochondrial membrane potential. C3P4 preferentially accumulated in mitochondria as measured by the gold content and substantially inhibited oxygen consumption rate and ATP production. These results further validated our hypothesis that targeting mitochondria would be promising to develop more potent anticancer agents. C3P4 may be further evaluated as a drug candidate for lung cancer treatment.

Water, in trace amounts, can greatly alter chemical and physical properties of mantle minerals and exert primary control on Earth’s dynamics. Quantifying how water is retained and distributed in Earth’s deep interior is essential to our understanding of Earth’s origin and evolution. While directly sampling Earth’s deep interior remains challenging, the experimental technique using laser-heated diamond anvil cell (LH-DAC) is likely the only method available to synthesize and recover analog specimens throughout Earth’s lower mantle conditions. The recovered samples, however, are typically of micron sizes and require high spatial resolution to analyze their water abundance. Here we use nano-scale secondary ion mass spectrometry (NanoSIMS) to characterize water content in bridgmanite, the most abundant mineral in Earth’s lower mantle. We have established two working standards of natural orthopyroxene that are likely suitable for calibrating water concentration in bridgmanite, i.e., A119(H2O) = 99 ± 13 μg/g (1SD) and A158(H2O) = 293 ± 23 μg/g (1SD). We find that matrix effect among orthopyroxene, olivine, and glass is less than 10%, while that between orthopyroxene and clinopyroxene can be up to 20%. Using our calibration, a bridgmanite synthesized by LH-DAC at 33 ± 1 GPa and 3,690 ± 120 K is measured to contain 1,099 ± 14 μg/g water, with partition coefficient of water between bridgmanite and silicate melt ∼0.025, providing the first measurement at such condition. Applying the unique analytical capability of NanoSIMS to minute samples recovered from LH-DAC opens a new window to probe water and other volatiles in Earth’s deep mantle.

Bacteria in nature are present in different lifestyles with distinct characteristics. Streptococcus mutans is the etiologic pathogen of dental caries and could easily gain access into the bloodstream after oral surgery and adopt a biofilm lifestyle, resulting in infective endocarditis. A growing amount of evidence have revealed that the large web-like structure composed of extracellular DNA and antimicrobial proteins released by neutrophils, named Neutrophil Extracellular Traps (NETs), play an active role in the defense against bacterial invasion. The present study demonstrated that NETs formation was discriminatively affected by S. mutans biofilm and its planktonic counterpart. The free-floating planktonic S. mutans exhibited an active NETs response, whereas the biofilm community exhibited a reverse negative NETs response. Besides, impaired biofilm killing correlated with the decrease in NETs production. Unlike planktonic cells, biofilm avoided the burst of reactive oxygen species (ROS) when co-culture with neutrophils, and the NADPH-oxidase pathway was partially involved. A mice infection model also supported the distinguishing response of neutrophils challenged by different lifestyles of S. mutans. In conclusion, different bacterial physiological states can affect the distinct response of the host–microbe interaction, thus contributing to the anti-pathogen immune response activation and immune surveillance survival.

Psoriasis can be provoked or exacerbated by environmental exposures such as certain microbiomes. The distinction between plaque psoriasis (PP) and guttate psoriasis (GP) in the skin or pharyngeal microbiota is not yet clear. High-throughput sequencing using Illumina MiSeq was used in this study to characterize skin and pharyngeal microbial composition in patients with PP [large PP (LPP, n = 62), small PP (SPP, n = 41)] and GP (n = 14). The alpha- and beta-diversity of skin microbiota LPP was similar to that of the SPP group, but different from the GP group. There were no differences in pharyngeal microbiota among the groups. According to linear discriminant analysis effect size (LEfSe) analysis, Staphylococcus, Stenotrophomonas, Enhydrobacter, Brevundimonas, and Allorhizobium–Neorhizobium–Pararhizobium–Rhizobium were the dominant genera of skin microbiota in PP. Diversity of skin microbiota correlated with Psoriasis Area and Severity Index (PASI). Moderate-to-severe psoriasis and mild psoriasis have different microbiota compositions. The skin microbiota may be related to the pharyngeal microbiota. Furthermore, two microbiota-based models could distinguish psoriasis subtypes with area under the receiver-operating characteristic curve (AUC-ROC) of 0.935 and 0.836, respectively. In conclusion, the skin microbiota in patients with LPP is similar to that in patients with SPP, but displays variations compared to that of GP, no differences are noted between subtypes in pharyngeal microbiota. Skin microbiota diversity correlated with PASI.

Internal tandem duplications (ITD) mutation within FMS-like tyrosine kinase 3 (FLT3), the most frequent mutation happens in almost 20% acute myeloid leukemia (AML) patients, always predicts a poor prognosis. As a small molecule tyrosine kinase inhibitor, sorafenib is clinically used for the treatment of advanced renal cell carcinoma (RCC), hepatocellular carcinoma (HCC), and differentiated thyroid cancer (DTC), with its preclinical and clinical activity demonstrated in the treatment of Fms-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD) mutant AML. Even though it shows a rosy future in the AML treatment, the short response duration remains a vital problem that leads to treatment failure. Rapid onset of drug resistance is still a thorny problem that we cannot overlook. Although the mechanisms of drug resistance have been studied extensively in the past years, there is still no consensus on the exact reason for resistance and without effective therapeutic regimens established clinically. My previous work reported that sorafenib-resistant FLT3-ITD mutant AML cells displayed mitochondria dysfunction, which rendered cells depending on glycolysis for energy supply. In my present one, we further illustrated that losing the target protein FLT3 and the continuously activated PI3K/Akt signaling pathway may be the reason for drug resistance, with sustained activation of PI3K/AKT signaling responsible for the highly glycolytic activity and adenosine triphosphate (ATP) generation. PI3K inhibitor, LY294002, can block PI3K/AKT signaling, further inhibit glycolysis to disturb ATP production, and finally induce cell apoptosis. This finding would pave the way to remedy the FLT3-ITD mutant AML patients who failed with FLT3 targeted therapy.

Introduction: Mental disorders represent serious public health concerns in the U.S. Compared with Whites, racial/ethnic minority adolescents are more likely to be affected by mental disorders but less likely to use mental health services. This systematic review aimed to summarize factors related to mental health service use among minority adolescents in the U.S. as identified in previous research.Methodology: Following the PRISMA guideline, we systematically searched seven databases for peer reviewed articles related to barriers and facilitators of mental health service use among racial/ethnic minority adolescents.Results: Thirty-two quantitative studies met our inclusion criteria, among which 12 studies (37.5%) sampled mostly Blacks or African Americans, 6 studies (18.7%) focused primarily on Hispanics or Latin/a/x, including Mexican Americans and Puerto Ricans, and 4 studies (12.5%) were mostly Asian Americans (e.g., Chinese, Vietnamese). Based on the socio-ecological framework, 21 studies (65.6%) identified adolescent-related barriers and facilitators of mental health service use, including biological (e.g., age, gender), clinical (e.g., symptom severity), behavioral (e.g., drug/alcohol use), and psychological characteristics (e.g., internal asset) of minority youth. Ten studies (31.3%) identified parents-related factors that influenced minority adolescent mental health service use, including parental perceptions and beliefs, family and parenting issues, and demographic characteristics. Primary factors at the therapist level included ethnic match between patient and practitioner, relationship with healthcare practitioners, and patient-therapist co-endorsement of etiological beliefs. Fifteen studies (46.9%) identified factors influencing minority adolescent mental health service use at the contextual/structural level, including household income, insurance status, and family structure. Lastly, acculturation and school experiences were major factors at the social/cultural level that influence minority adolescent service use.Conclusion: More empirical studies are needed to understand the mechanism underlying minority adolescents' unmet mental health service needs. Culturally competent interventions are warranted to engage minority adolescents with mental disorders into treatment.

Children of immigrants are often considered to be at increased risk of mental health problems due to families' immigration-related stress and perceived discrimination and prejudice from the host country. However, many studies found them to have better developmental outcomes than children with native-born parents in the U.S. This study aims to unfold this paradoxical phenomenon using data from a population-based cohort of children born in large U.S. cities. Specifically, we investigated differences in mental health outcomes between children of immigrants and those with native-born parents, stratified by children's race-ethnicity. We also explored the mediating role of child maltreatment risk in the association of parental nativity status and race-ethnicity with children's mental health. Our findings supported the immigrant paradox, with better self-reported and parent-reported internalizing and externalizing outcomes in Hispanic and Black children of immigrants than their same race-ethnicity peers and White children of native-born. Such immigrant-native variations were partially explained by parents' physically and psychologically abusive behaviors. Hispanic and Black children with immigrant parents were less likely to be physically or psychologically abused than their peers of native-born at ages 4–5, which translated into mental health advantages of children of immigrants at age 9. Our findings shed light on future research to further clarify the mechanism underlying different parenting practices between same race-ethnicity immigrants and native-born families so that culturally responsive interventions can be developed to safeguard racial-ethnic minority children's mental health.

Machine learning is about finding patterns and making predictions from raw data. In this study, we aimed to achieve two goals by utilizing the modern logistic regression model as a statistical tool and classifier. First, we analyzed the associations between Major Depressive Episode with Severe Impairment (MDESI) in adolescents with a list of broadly defined sociodemographic characteristics. Using findings from the logistic model, the second and ultimate goal was to identify the potential MDESI cases using a logistic model as a classifier (i.e., a predictive mechanism). Data on adolescents aged 12–17 years who participated in the National Survey on Drug Use and Health (NSDUH), 2011–2017, were pooled and analyzed. The logistic regression model revealed that compared with males and adolescents aged 12-13, females and those in the age groups of 14-15 and 16-17 had higher risk of MDESI. Blacks and Asians had lower risk of MDESI than Whites. Living in single-parent household, having less authoritative parents, having negative school experiences further increased adolescents' risk of having MDESI. The predictive model successfully identified 66% of the MDESI cases (recall rate) and accurately identified 72% of the MDESI and MDESI-free cases (accuracy rate) in the training data set. The rates of both recall and accuracy remained about the same (66 and 72%) using the test data. Results from this study confirmed that the logistic model, when used as a classifier, can identify potential cases of MDESI in adolescents with acceptable recall and reasonable accuracy rates. The algorithmic identification of adolescents at risk for depression may improve prevention and intervention.