BackgroundThe crude extract of the fruit bearing plant, Physalis peruviana (golden berry), demonstrated anti-hepatoma and anti-inflammatory activities. However, the cellular mechanism involved in this process is still unknown.MethodsHerein, we isolated the main pure compound, 4β-Hydroxywithanolide (4βHWE) derived from golden berries, and investigated its antiproliferative effect on a human lung cancer cell line (H1299) using survival, cell cycle, and apoptosis analyses. An alkaline comet-nuclear extract (NE) assay was used to evaluate the DNA damage due to the drug.ResultsIt was shown that DNA damage was significantly induced by 1, 5, and 10 μg/mL 4βHWE for 2 h in a dose-dependent manner (p < 0.005). A trypan blue exclusion assay showed that the proliferation of cells was inhibited by 4βHWE in both dose- and time-dependent manners (p < 0.05 and 0.001 for 24 and 48 h, respectively). The half maximal inhibitory concentrations (IC50) of 4βHWE in H1299 cells for 24 and 48 h were 0.6 and 0.71 μg/mL, respectively, suggesting it could be a potential therapeutic agent against lung cancer. In a flow cytometric analysis, 4βHWE produced cell cycle perturbation in the form of sub-G1 accumulation and slight arrest at the G2/M phase with 1 μg/mL for 12 and 24 h, respectively. Using flow cytometric and annexin V/propidium iodide immunofluorescence double-staining techniques, these phenomena were proven to be apoptosis and complete G2/M arrest for H1299 cells treated with 5 μg/mL for 24 h.ConclusionsIn this study, we demonstrated that golden berry-derived 4βHWE is a potential DNA-damaging and chemotherapeutic agent against lung cancer.

The domain of unknown function 692 (DUF692) is an emerging family of post-translational modification enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products. Members of this family are multinuclear iron-containing enzymes, and only two members have been functionally characterized to date: MbnB and TglH. Here, we used bioinformatics to select another member of the DUF692 family, ChrH, that is encoded in the genomes of the Chryseobacterium genus along with a partner protein ChrI. We structurally characterized the ChrH reaction product and show that the enzyme complex catalyzes an unprecedented chemical transformation that results in the formation of a macrocycle, an imidazolidinedione heterocycle, two thioaminals, and a thiomethyl group. Based on isotopic labeling studies, we propose a mechanism for the four-electron oxidation and methylation of the substrate peptide. This work identifies the first SAM-dependent reaction catalyzed by a DUF692 enzyme complex, further expanding the repertoire of remarkable reactions catalyzed by these enzymes. Based on the three currently characterized DUF692 family members, we suggest the family be called multinuclear non-heme iron dependent oxidative enzymes (MNIOs).

Objectives.-A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors have combined these capabilities into an online (i.e., web-based) pure-tone audiogram estimator intended to empower researchers and clinicians with advanced hearing tests without the need for custom programming. The objective of this study is to assess the accuracy and reliability of this new online machine learning audiogram method relative to a commonly used hearing threshold estimation technique also implemented online for the first time in the same platform.Design.-The authors performed air-conduction pure-tone audiometry on 21 participants between the ages of 19 and 79 years (mean 41, standard deviation 21) exhibiting a wide range of hearing abilities. For each ear, two repetitions of online machine learning audiogram estimation and two repetitions of online modified Hughson-Westlake ascending-descending audiogram estimation were acquired by an audiologist using the online software tools. The estimated hearing thresholds of these two techniques were compared at standard audiogram frequencies (i.e., 0.25, 0.5, 1, 2, 4, 8 kHz).Results.-The two threshold estimation methods delivered very similar threshold estimates at standard audiogram frequencies. Specifically, the mean absolute difference between threshold estimates was 3.24 ± 5.15 dB. The mean absolute differences between repeated measurements of the online machine learning procedure and between repeated measurements of the Hughson-Westlake procedure were 2.85 ± 6.57 dB and 1.88 ± 3.56 respectively. The machine learning method generated estimates of both threshold and spread (i.e., the inverse of psychometric slope)

Behavioral testing in perceptual or cognitive domains requires querying a subject multiple times in order to quantify his or her ability in the corresponding domain. These queries must be conducted sequentially, and any additional testing domains are also typically tested sequentially, such as with distinct tests comprising a test battery. As a result, existing behavioral tests are often lengthy and do not offer comprehensive evaluation. The use of active machine-learning kernel methods for behavioral assessment provides extremely flexible yet efficient estimation tools to more thoroughly investigate perceptual or cognitive processes without incurring the penalty of excessive testing time. Audiometry represents perhaps the simplest test case to demonstrate the utility of these techniques. In pure-tone audiometry, hearing is assessed in the two-dimensional input space of frequency and intensity, and the test is repeated for both ears. Although an individual's ears are not linked physiologically, they share many features in common that lead to correlations suitable for exploitation in testing. The bilateral audiogram estimates hearing thresholds in both ears simultaneously by conjoining their separate input domains into a single search space, which can be evaluated efficiently with modern machine-learning methods. The result is the introduction of the first conjoint psychometric function estimation procedure, which consistently delivers accurate results in significantly less time than sequential disjoint estimators.

The syntheses of peptidoglycan (PG)-derived peptides containing meso-diaminopimelic acid (meso-Dap) are typically quite lengthy due to the need to prepare orthogonally protected meso-Dap. In this work, the preparation of the PG pentapeptide containing the isosteric analog meso-oxa-Dap is described. The synthesis relies on the ring opening of a peptide embedded aziridine via the attack of a serine residue. The pentapeptide was attached to a GlcNAc-anhydro-MurNAc disaccharide, to produce a putative substrate for the AmpG pore protein.