Displaying publications 21 - 26 of 26 in total

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  1. Cameron NA, Freaney PM, Wang MC, Perak AM, Dolan BM, O'Brien MJ, et al.
    Circulation, 2022 Feb 15;145(7):549-551.
    PMID: 35157521 DOI: 10.1161/CIRCULATIONAHA.121.057107
  2. Mehta PM, Wang MC, Cameron NA, Freaney PM, Perak AM, Shah NS, et al.
    Am J Prev Med, 2023 Dec;65(6):1184-1186.
    PMID: 37552145 DOI: 10.1016/j.amepre.2023.07.007
  3. Huang X, Lee K, Wang MC, Shah NS, Perak AM, Venkatesh KK, et al.
    JAMA Pediatr, 2024 Jan 01;178(1):65-72.
    PMID: 37955913 DOI: 10.1001/jamapediatrics.2023.4907
    IMPORTANCE: Preterm birth is a major contributor to neonatal morbidity and mortality, and considerable differences exist in rates of preterm birth among maternal racial and ethnic groups. Emerging evidence suggests pregnant individuals born outside the US have fewer obstetric complications than those born in the US, but the intersection of maternal nativity with race and ethnicity for preterm birth is not well studied.

    OBJECTIVE: To determine if there is an association between maternal nativity and preterm birth rates among nulliparous individuals, and whether that association differs by self-reported race and ethnicity of the pregnant individual.

    DESIGN, SETTING, AND PARTICIPANTS: This was a nationwide, cross-sectional study conducted using National Center for Health Statistics birth registration records for 8 590 988 nulliparous individuals aged 15 to 44 years with singleton live births in the US from 2014 to 2019. Data were analyzed from March to May 2022.

    EXPOSURES: Maternal nativity (non-US-born compared with US-born individuals as the reference, wherein US-born was defined as born within 1 of the 50 US states or Washington, DC) in the overall sample and stratified by self-reported ethnicity and race, including non-Hispanic Asian and disaggregated Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Pacific Islander, Vietnamese, and other Asian), non-Hispanic Black, Hispanic and disaggregated Hispanic subgroups (Cuban, Mexican, Puerto Rican, and other Hispanic), and non-Hispanic White.

    MAIN OUTCOMES AND MEASURES: The primary outcome was preterm birth (<37 weeks of gestation) and the secondary outcome was very preterm birth (<32 weeks of gestation).

    RESULTS: Of 8 590 988 pregnant individuals included (mean [SD] age at delivery, 28.3 [5.8] years in non-US-born individuals and 26.2 [5.7] years in US-born individuals; 159 497 [2.3%] US-born and 552 938 [31.2%] non-US-born individuals self-identified as Asian or Pacific Islander, 1 050 367 [15.4%] US-born and 178 898 [10.1%] non-US-born individuals were non-Hispanic Black, 1 100 337 [16.1%] US-born and 711 699 [40.2%] non-US-born individuals were of Hispanic origin, and 4 512 294 [66.1%] US-born and 328 205 [18.5%] non-US-born individuals were non-Hispanic White), age-standardized rates of preterm birth were lower among non-US-born individuals compared with US-born individuals (10.2%; 95% CI, 10.2-10.3 vs 10.9%; 95% CI, 10.9-11.0) with an adjusted odds ratio (aOR) of 0.90 (95% CI, 0.89-0.90). The greatest relative difference was observed among Japanese individuals (aOR, 0.69; 95% CI, 0.60-0.79) and non-Hispanic Black individuals (aOR, 0.74; 0.73-0.76) individuals. Non-US-born Pacific Islander individuals experienced higher preterm birth rates compared with US-born Pacific Islander individuals (aOR, 1.15; 95% CI, 1.04-1.27). Puerto Rican individuals born in Puerto Rico compared with those born in US states or Washington, DC, also had higher preterm birth rates (aOR, 1.07; 95% CI, 1.03-1.12).

    CONCLUSIONS AND RELEVANCE: Overall preterm birth rates were lower among non-US-born individuals compared with US-born individuals. However, there was substantial heterogeneity in preterm birth rates across maternal racial and ethnic groups, particularly among disaggregated Asian and Hispanic subgroups.

  4. Kour D, Khan SS, Kumari S, Singh S, Khan RT, Kumari C, et al.
    PMID: 38421484 DOI: 10.1007/s12223-024-01147-2
    The field of nanotechnology has the mysterious capacity to reform every subject it touches. Nanotechnology advancements have already altered a variety of scientific and industrial fields. Nanoparticles (NPs) with sizes ranging from 1 to 100 nm (nm) are of great scientific and commercial interest. Their functions and characteristics differ significantly from those of bulk metal. Commercial quantities of NPs are synthesized using chemical or physical methods. The use of the physical and chemical approaches remained popular for many years; however, the recognition of their hazardous effects on human well-being and conditions influenced serious world perspectives for the researchers. There is a growing need in this field for simple, non-toxic, clean, and environmentally safe nanoparticle production methods to reduce environmental impact and waste and increase energy productivity. Microbial nanotechnology is relatively a new field. Using various microorganisms, a wide range of nanoparticles with well-defined chemical composition, morphology, and size have been synthesized, and their applications in a wide range of cutting-edge technological areas have been investigated. Green synthesis of the nanoparticles is cost-efficient and requires low maintenance. The present review highlights the synthesis of the nanoparticles by different microbes, their characterization, and their biotechnological potential. It further deals with the applications in biomedical, food, and textile industries as well as its role in biosensing, waste recycling, and biofuel production.
  5. Venkatesh KK, Perak AM, Wu J, Catalano P, Josefson JL, Costantine MM, et al.
    Am J Obstet Gynecol, 2024 May 02.
    PMID: 38703941 DOI: 10.1016/j.ajog.2024.04.037
    BACKGROUND: Adverse pregnancy outcomes, including hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM), influence maternal cardiovascular heath (CVH) long after pregnancy, but their relationship to offspring CVH following in utero exposure remains uncertain.

    OBJECTIVE: To examine associations of HDP or GDM with offspring CVH in early adolescence.

    STUDY DESIGN: This analysis used data from the prospective Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study from 2000 to 2006 and the HAPO Follow-Up Study from 2013 to 2016. This analysis included 3,317 mother-child dyads from 10 field centers, comprising 70.8% of HAPO Follow-Up Study participants. Those with pregestational diabetes and chronic hypertension were excluded. The exposures were having any HDP or GDM compared with not having HDP or GDM, respectively (reference). The outcome was offspring CVH at ages 10 to 14 years, based on four metrics: body mass index, blood pressure, total cholesterol level, and glucose level. Each metric was categorized as ideal, intermediate, or poor using a framework provided by the American Heart Association. The outcome was primarily defined as having at least one CVH metric that was non-ideal versus all ideal (reference), and secondarily as the number of non-ideal CVH metrics: at least one intermediate metric, one poor metric, or at least two poor metrics versus all ideal (reference). Modified Poisson regression with robust error variance was used and adjusted for covariates at pregnancy enrollment, including field center, parity, age, gestational age, alcohol or tobacco use, child's assigned sex at birth, and child's age at follow-up.

    RESULTS: Among 3,317 maternal-child dyads, the median (IQR) ages were 30.4 (25.6, 33.9) years for pregnant individuals and 11.6 (10.9, 12.3) years for children. During pregnancy, 10.4% of individuals developed HDP and 14.6% developed GDM. At follow-up, 55.5% of offspring had at least one non-ideal CVH metric. In adjusted models, having HDP (aRR 1.14; 95% CI 1.04, 1.25) or having GDM (aRR 1.10; 95% CI 1.02, 1.19) was associated with greater risk that offspring developed less-than-ideal CVH at ages 10 to 14 years. The above associations strengthened in magnitude as the severity of adverse CVH metrics increased (i.e., with the outcome measured as >1 intermediate, 1 poor, and >2 poor adverse metrics), albeit the only statistically significant association was with the "1-poor-metric" exposure.

    CONCLUSONS: In this multi-national prospective cohort, pregnant individuals who experienced either HDP and GDM were at significantly increased risk of having offspring with worse CVH in early adolescence. Reducing adverse pregnancy outcomes and increasing surveillance with targeted interventions after an adverse pregnancy outcome should be studied as potential avenues to enhance long-term cardiovascular health in the offspring exposed in utero.

  6. Ng ML, Majid AMSA, Yee SM, Natesan V, Basheer MKA, Gnanasekaran A, et al.
    Support Care Cancer, 2024 May 06;32(6):331.
    PMID: 38710920 DOI: 10.1007/s00520-024-08536-w
    AIM: We evaluated the efficacy and safety of Nuvastatic™ (C5OSEW5050ESA) in improving cancer-related fatigue (CRF) among cancer patients.

    METHODS: This multicenter randomized double-blind placebo-controlled phase 2 trial included 110 solid malignant tumor patients (stage II-IV) undergoing chemotherapy. They were randomly selected and provided oral Nuvastatic™ 1000 mg (N = 56) or placebo (N = 54) thrice daily for 9 weeks. The primary outcomes were fatigue (Brief Fatigue Inventory (BFI)) and Visual Analog Scale for Fatigue (VAS-F)) scores measured before and after intervention at baseline and weeks 3, 6, and 9. The secondary outcomes were mean group difference in the vitality subscale of the Medical Outcome Scale Short Form-36 (SF-36) and urinary F2-isoprostane concentration (an oxidative stress biomarker), Eastern Cooperative Oncology Group scores, adverse events, and biochemical and hematologic parameters. Analysis was performed by intention-to-treat (ITT). Primary and secondary outcomes were assessed by two-way repeated-measures analysis of variance (mixed ANOVA).

    RESULTS: The Nuvastatic™ group exhibited an overall decreased fatigue score compared with the placebo group. Compared with the placebo group, the Nuvastatic™ group significantly reduced BFI-fatigue (BFI fatigue score, F (1.4, 147) = 16.554, p 

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