Association between heart rate variability metrics from a smartwatch and self-reported depression and anxiety symptoms: a four-week longitudinal study.

Background: Elucidating the association between heart rate variability (HRV) metrics obtained through non-invasive methods and mental health symptoms could provide an accessible approach to mental health monitoring. This study explores the correlation between HRV, estimated using photoplethysmography (PPG) signals, and self-reported symptoms of depression and anxiety. Methods: A 4-week longitudinal study was conducted among 47 participants. Time-domain and frequency-domain HRV metrics were derived from PPG signals collected via smartwatches. Mental health symptoms were evaluated using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) at baseline, week 2, and week 4. Results: Among the investigated HRV metrics, RMSSD, SDNN, SDSD, LF, and the LF/HF ratio were significantly associated with the PHQ-9 score, although the number of significant correlations was relatively small. Furthermore, only SDNN, SDSD and LF showed significant correlations with the GAD-7 score. All HRV metrics showed negative correlations with self-reported clinical symptoms. Conclusions: Our findings indicate the potential of PPG-derived HRV metrics in monitoring mental health, thereby providing a foundation for further research. Notably, parasympathetically biased HRV metrics showed weaker correlations with depression and anxiety scores. Future studies should validate these findings in clinically diagnosed patients.

Imputing missing sleep data from wearables with neural networks in real-world settings.

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles. Based on this, we develop two approaches: the individual approach imputes missing data based on the data from only one participant, while the global approach imputes missing data based on the data across multiple participants. Our models are tested with shift and non-shift workers' data from three independent hospitals. Both approaches can accurately impute missing data up to 24 hours of long dataset (>50 days) even for shift workers with extremely irregular sleep-wake patterns (AUC > 0.86). On the other hand, for short dataset (~15 days), only the global model is accurate (AUC > 0.77). Our approach can be used to help clinicians monitor sleep-wake cycles of patients with sleep disorders outside of laboratory settings without relying on sleep diaries, ultimately improving sleep health outcomes.

Social dimensions impact individual sleep quantity and quality.

While sleep positively impacts well-being, health, and productivity, the effects of societal factors on sleep remain underexplored. Here we analyze the sleep of 30,082 individuals across 11 countries using 52 million activity records from wearable devices. Our data are consistent with past studies of gender and age-associated sleep characteristics. However, our analysis of wearable device data uncovers differences in recorded vs. self-reported bedtime and sleep duration. The dataset allowed us to study how country-specific metrics such as GDP and cultural indices relate to sleep in groups and individuals. Our analysis indicates that diverse sleep metrics can be represented by two dimensions: sleep quantity and quality. We find that 55% of the variation in sleep quality, and 63% in sleep quantity, are explained by societal factors. Within a societal boundary, individual sleep experience was modified by factors like exercise. Increased exercise or daily steps were associated with better sleep quality (for example, faster sleep onset and less time awake in bed), especially in countries like the U.S. and Finland. Understanding how social norms relate to sleep will help create strategies and policies that enhance the positive impacts of sleep on health, such as productivity and well-being.

Mechanical stimulation reprograms the sorghum internode transcriptome and broadly alters hormone homeostasis.

Stem structural failure, or lodging, affects many crops including sorghum, and can cause large yield losses. Lodging is typically caused by mechanical forces associated with severe weather like high winds, but exposure to sub-catastrophic forces may strengthen stems and improve lodging resistance. The responses of sorghum internodes at different developmental stages were examined at 2 and 26 h after initiating moderate mechanical stimulation with an automated apparatus. Transcriptome profiling revealed that mechanical stimulation altered the expression of over 900 genes, including transcription factors, cell wall-related and hormone signaling-related genes. IAA, GA1 and ABA abundances generally declined following mechanical stimulation, while JA increased. Weighted Gene Co-expression Network Analysis (WGCNA) identified three modules significantly enriched in GO terms associated with cell wall biology, hormone signaling and general stress responses, which were highly correlated with mechanical stimulation and with biomechanical and geometrical traits documented in a separate study. Additionally, mechanical stimulation-triggered responses were dependent on the developmental stage of the internode and the duration of stimulation. This study provides insights into the underlying mechanisms of plant hormone-regulated thigmomorphogenesis in sorghum stems. The critical biological processes and hub genes described here may offer opportunities to improve lodging resistance in sorghum and other crops.

Real-World Outcomes of Ruxolitinib in Patients With Myelofibrosis Focusing on Red Blood Cell Transfusion: A Multicenter Study From the MPN Working Party of the Korean Society of Hematology.

INTRODUCTION/BACKGROUND: Ruxolitinib is an established treatment for myelofibrosis (MF) that has demonstrated clinical benefit by reducing spleen size and debilitating MF-related symptoms. However, despite the efficacy of ruxolitinib, anemia remains a major adverse event that causes dose modification or discontinuation in real-world practice. Additionally, dependence on red blood cell (RBC) transfusion (TF) is common during treatment; therefore, we explored the outcome of ruxolitinib therapy with a primary focus on RBC TF. PATIENTS/METHODS: We retrospectively reviewed the medical records of 123 MF patients treated with ruxolitinib between January 2012 and April 2020 at eight academic centers in Korea. RESULTS: At ruxolitinib initiation, 38 patients (30.9%) underwent ≥ 2 units of RBC TF over 8 weeks. The most common reason for permanent discontinuation was intolerant anemia (10/63, 15.9%). The most common reasons for temporary interruption were nonhematologic toxicity (26/55, 21.1%), anemia (23/55, 18.7%) and thrombocytopenia (13/55, 10.6%). Among the 123 patients in the study, 57 (46.3%), 42 (34.1%), and 40 patients (32.5%) who were receiving or stopped ruxolitinib therapy had a status of RBC TF dependence, long-term RBC TF dependence, or severe RBC TF dependence, respectively. The presence of ≥ 2 units of RBC transfusion over 8 weeks at ruxolitinib initiation was an independent risk factor for persistent RBC TF dependence. CONCLUSION: The requirement for RBC TF is commonly encountered during treatment of MF with ruxolitinib, particularly among those with pre-existing ≥ 2 units of RBC TF over 8 weeks. For those patients, overcoming the barrier of maintenance TF is demanding.

SERS-based dual-mode DNA aptasensors for rapid classification of SARS-CoV-2 and influenza A/H1N1 infection.

We developed a dual-mode surface-enhanced Raman scattering (SERS)-based aptasensor that can accurately diagnose and distinguish severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/H1N1 at the same time. Herein, DNA aptamers that selectively bind to SARS-CoV-2 and influenza A/H1N1 were immobilized together on Au nanopopcorn substrate. Raman reporters (Cy3 and RRX), attached to the terminal of DNA aptamers, could generate strong SERS signals in the nanogap of the Au nanopopcorn substrate. Additionally, the internal standard Raman reporter (4-MBA) was immobilized on the Au nanopopcorn substrate along with aptamer DNAs to reduce errors caused by changes in the measurement environment. When SARS-CoV-2 or influenza A virus approaches the Au nanopopcorn substrate, the corresponding DNA aptamer selectively detaches from the substrate due to the significant binding affinity between the corresponding DNA aptamer and the virus. As a result, the related SERS intensity decreases with increasing target virus concentration. Thus, it is possible to determine whether a suspected patient is infected with SARS-CoV-2 or influenza A using this SERS-based DNA aptasensor. Furthermore, this sensor enables a quantitative evaluation of the target virus concentration with high sensitivity without being affected by cross-reactivity. Therefore, this SERS-based diagnostic platform is considered a conceptually new diagnostic tool that rapidly discriminates against these two respiratory diseases to prevent their spread.

COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication.

BACKGROUND: COVID-19, caused by SARS-CoV-2, has led to a global pandemic. The World Health Organization has also declared an infodemic (ie, a plethora of information regarding COVID-19 containing both false and accurate information circulated on the internet). Hence, it has become critical to test the veracity of information shared online and analyze the evolution of discussed topics among citizens related to the pandemic. OBJECTIVE: This research analyzes the public discourse on COVID-19. It characterizes risk communication patterns in four Asian countries with outbreaks at varying degrees of severity: South Korea, Iran, Vietnam, and India. METHODS: We collected tweets on COVID-19 from four Asian countries in the early phase of the disease outbreak from January to March 2020. The data set was collected by relevant keywords in each language, as suggested by locals. We present a method to automatically extract a time-topic cohesive relationship in an unsupervised fashion based on natural language processing. The extracted topics were evaluated qualitatively based on their semantic meanings. RESULTS: This research found that each government's official phases of the epidemic were not well aligned with the degree of public attention represented by the daily tweet counts. Inspired by the issue-attention cycle theory, the presented natural language processing model can identify meaningful transition phases in the discussed topics among citizens. The analysis revealed an inverse relationship between the tweet count and topic diversity. CONCLUSIONS: This paper compares similarities and differences of pandemic-related social media discourse in Asian countries. We observed multiple prominent peaks in the daily tweet counts across all countries, indicating multiple issue-attention cycles. Our analysis identified which topics the public concentrated on; some of these topics were related to misinformation and hate speech. These findings and the ability to quickly identify key topics can empower global efforts to fight against an infodemic during a pandemic.

Correction: COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication.

[This corrects the article DOI: 10.2196/23272.].

PASS-DIA: A Data-Independent Acquisition Approach for Discovery Studies.

A data-independent acquisition (DIA) approach is being increasingly adopted as a promising strategy for identification and quantitation of proteomes. As most DIA data sets are acquired with wide isolation windows, highly complex MS/MS spectra are generated, which negatively impacts obtaining peptide information through classical protein database searches. Therefore, the analysis of DIA data mainly relies on the evidence of the existence of peptides from prebuilt spectral libraries. Consequently, one major weakness of this method is that it does not account for peptides that are not included in the spectral library, precluding the use of DIA for discovery studies. Here, we present a strategy termed Precursor ion And Small Slice-DIA (PASS-DIA) in which MS/MS spectra are acquired with small isolation windows (slices) and MS/MS spectra are interpreted with accurately determined precursor ion masses. This method enables the direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was observed to be superior to both data-dependent acquisition (DDA) and conventional DIA experiments with 69 and 48% additional protein identifications, respectively. Application of PASS-DIA for the analysis of post-translationally modified peptides again highlighted its superior performance in characterizing phosphopeptides (77% more), N-terminal acetylated peptides (56% more), and N-glycopeptides (83% more) as compared to DDA alone. Finally, the use of PASS-DIA to characterize a rare proteome of human fallopian tube organoids enabled 34% additional protein identifications than DDA alone and revealed biologically relevant pathways including low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool that outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that the PASS-DIA method is an important strategy for discovery-type studies when deeper proteome characterization is required.

Treatment with intravenous busulfan, melphalan, and etoposide followed by autologous stem cell transplantation in patients with non-Hodgkin's lymphoma: a multicenter study from the consortium for improving survival of lymphoma.

Several high-dose therapy (HDT) conditioning regimens have been used to treat non-Hodgkin's lymphoma (NHL), such as bis-chloroethylnitrosourea (BCNU)/etoposide/cytosine arabinoside/melphalan (BEAM), BCNU/etoposide/cytosine arabinoside/cyclophosphamide (BEAC), and cyclophosphamide/BCNU/etoposide (CBV). BCNU is an active drug in HDT of NHL, but the supply is limited in some countries, including Korea. Busulfan has been used in allogeneic and autologous stem cell transplantation (ASCT). This phase II study evaluated the efficacy of busulfan/melphalan/etoposide (BuME) as a conditioning regimen for HDT in relapsed or high-risk NHL. The regimen consisted of intravenous busulfan (3.2 mg/kg/day) on days -8, -7, and -6, etoposide (400 mg/m2 /day) on days -5 and -4, and melphalan (50 mg/m2 /day) on days -3 and -2. A total of 46 patients were included in the study, with 36 (78.3%) achieving a complete response after ASCT. The 2-year progression-free survival (PFS) and overall survival (OS) rates for all patients were 46.7% (95% CI, 31.8-60.4%) and 63.7% (95% CI, 47.7-76.0%), respectively. There was no development of veno-occlusive disease and no treatment-related deaths within 100 days after ASCT. These results indicate that a BuME regimen is well-tolerated and effective for patients with relapsed or high-risk NHL, and may be comparable to some previously used regimens. This regimen may be useful as a substitute for BCNU-containing regimens.

Clustering Insomnia Patterns by Data From Wearable Devices: Algorithm Development and Validation Study.

BACKGROUND: As societies become more complex, larger populations suffer from insomnia. In 2014, the US Centers for Disease Control and Prevention declared that sleep disorders should be dealt with as a public health epidemic. However, it is hard to provide adequate treatment for each insomnia sufferer, since various behavioral characteristics influence symptoms of insomnia collectively. OBJECTIVE: We aim to develop a neural-net based unsupervised user clustering method towards insomnia sufferers in order to clarify the unique traits for each derived groups. Unlike the current diagnosis of insomnia that requires qualitative analysis from interview results, the classification of individuals with insomnia by using various information modalities from smart bands and neural-nets can provide better insight into insomnia treatments. METHODS: This study, as part of the precision psychiatry initiative, is based on a smart band experiment conducted over 6 weeks on individuals with insomnia. During the experiment period, a total of 42 participants (19 male; average age 22.00 [SD 2.79]) from a large university wore smart bands 24/7, and 3 modalities were collected and examined: sleep patterns, daily activities, and personal demographics. We considered the consecutive daily information as a form of images, learned the latent variables of the images via a convolutional autoencoder (CAE), and clustered and labeled the input images based on the derived features. We then converted consecutive daily information into a sequence of the labels for each subject and finally clustered the people with insomnia based on their predominant labels. RESULTS: Our method identified 5 new insomnia-activity clusters of participants that conventional methods have not recognized, and significant differences in sleep and behavioral characteristics were shown among groups (analysis of variance on rank: F4,37=2.36, P=.07 for the sleep_min feature; F4,37=9.05, P<.001 for sleep_efficiency; F4,37=8.16, P<.001 for active_calorie; F4,37=6.53, P<.001 for walks; and F4,37=3.51, P=.02 for stairs). Analyzing the consecutive data through a CAE and clustering could reveal intricate connections between insomnia and various everyday activity markers. CONCLUSIONS: Our research suggests that unsupervised learning allows health practitioners to devise precise and tailored interventions at the level of data-guided user clusters (ie, precision psychiatry), which could be a novel solution to treating insomnia and other mental disorders.

C/N/O/S stable isotopic and chemometric analyses for determining the geographical origin of Panax ginseng cultivated in Korea.

BACKGROUND: The geographical origin of Panax ginseng Meyer, a valuable medicinal plant, is important to both ginseng producers and consumers in the context of economic profit and human health benefits. We, therefore, aimed to discriminate between the cultivation regions of ginseng using the stable isotope ratios of C, N, O, and S, which are abundant bioelements in living organisms. METHODS: Six Korean ginseng cultivars (3-yr-old roots) were collected from five different regions in Korea. The C, N, O, and S stable isotope ratios in ginseng roots were measured by isotope ratio mass spectrometry, and then these isotope ratio profiles were statistically analyzed using chemometrics. RESULTS: The various isotope ratios found in P. ginseng roots were significantly influenced by region, cultivar, and the interactions between these two factors (p ≤ 0.001). The variation in δ15N and δ13C in ginseng roots was significant for discriminating between different ginseng cultivation regions, and δ18O and δ34S were also affected by both altitude and proximity to coastal areas. Chemometric model results tested in this study provided discrimination between the majority of different cultivation regions. Based on the external validation, this chemometric model also showed good model performance (R 2 = 0.853 and Q 2 = 0.738). CONCLUSION: Our case study elucidates the variation of C, N, O, and S stable isotope ratios in ginseng root depending on cultivation region. Hence, the analysis of stable isotope ratios is a suitable tool for discrimination between the regional origins of ginseng samples from Korea, with potential application to other countries.

Differential processing of HIV envelope glycans on the virus and soluble recombinant trimer.

As the sole target of broadly neutralizing antibodies (bnAbs) to HIV, the envelope glycoprotein (Env) trimer is the focus of vaccination strategies designed to elicit protective bnAbs in humans. Because HIV Env is densely glycosylated with 75-90 N-glycans per trimer, most bnAbs use or accommodate them in their binding epitope, making the glycosylation of recombinant Env a key aspect of HIV vaccine design. Upon analysis of three HIV strains, we here find that site-specific glycosylation of Env from infectious virus closely matches Envs from corresponding recombinant membrane-bound trimers. However, viral Envs differ significantly from recombinant soluble, cleaved (SOSIP) Env trimers, strongly impacting antigenicity. These results provide a benchmark for virus Env glycosylation needed for the design of soluble Env trimers as part of an overall HIV vaccine strategy.

Global site-specific analysis of glycoprotein N-glycan processing.

N-glycans contribute to the folding, stability and functions of the proteins they decorate. They are produced by transfer of the glycan precursor to the sequon Asn-X-Thr/Ser, followed by enzymatic trimming to a high-mannose-type core and sequential addition of monosaccharides to generate complex-type and hybrid glycans. This process, mediated by the concerted action of multiple enzymes, produces a mixture of related glycoforms at each glycosite, making analysis of glycosylation difficult. To address this analytical challenge, we developed a robust semiquantitative mass spectrometry (MS)-based method that determines the degree of glycan occupancy at each glycosite and the proportion of N-glycans processed from high-mannose type to complex type. It is applicable to virtually any glycoprotein, and a complete analysis can be conducted with 30 µg of protein. Here, we provide a detailed description of the method that includes procedures for (i) proteolytic digestion of glycoprotein(s) with specific and nonspecific proteases; (ii) denaturation of proteases by heating; (iii) sequential treatment of the glycopeptide mixture with two endoglycosidases, Endo H and PNGase F, to create unique mass signatures for the three glycosylation states; (iv) LC-MS/MS analysis; and (v) data analysis for identification and quantitation of peptides for the three glycosylation states. Full coverage of site-specific glycosylation of glycoproteins is achieved, with up to thousands of high-confidence spectra hits for each glycosite. The protocol can be performed by an experienced technician or student/postdoc with basic skills for proteomics experiments and takes ∼7 d to complete.

Flavonoid glycosides from leaves and straw of Oryza sativa and their effects of cytotoxicity on a macrophage cell line and allelopathic on weed germination.

Five new flavonoids namely, 5-hydroxy-6-isoprenyl-7,4'-dimethoxyflavonol-3-O-ß-d-arabinofuranoside (1), 5,7-dihydroxy-4'-methoxyflavone-7-O-ß-d-arabinopyranosyl-2''-n-decan-1'''-oate (2), 3-butanoyl-5,6,8-trihydroxy-7,4'-dimethoxyflavonol--5-O-ß-d-glucopyranoside (3), 7, 4'-dimethoxy-5-hydroxyflavone-5-O-α-d-arabinopyranosyl-(2'' → 1''')-O-α-d-arabinopyranoside (4), and 5,6-dihydroxy-7, 4'-dimethoxyflavone-5-O-α-d-glucopyranoside (5), together with two known compounds, were isolated from the methanol extract of Oryza sativa leaves and straw. Their structures of new compounds were elucidated by 1D and 2D NMR spectral methods, viz: COSY, HMBC and HSQC aided by mass techniques and IR spectroscopy. The cytotoxicity of these compounds (1-7) were assessed by using (RAW 264.7) mouse macrophages cell line, and allelopathic effects of compounds (1-7) on the germination characteristics of barnyardgrass (Echinochloa oryzicola) and pigweed (Chenopodium album L.) were also evaluated. The compounds 1, 6 and 7 showed cytotoxicity and compounds 1-7 exhibited significant inhibitory activity on the seed germination of two weed species.

Geographic authentication of Asian rice (Oryza sativa L.) using multi-elemental and stable isotopic data combined with multivariate analysis.

Rice (Oryza sativa L.) is the world's third largest food crop after wheat and corn. Geographic authentication of rice has recently emerged asan important issue for enhancing human health via food safety and quality assurance. Here, we aimed to discriminate rice of six Asian countries through geographic authentication using combinations of elemental/isotopic composition analysis and chemometric techniques. Principal components analysis could distinguish samples cultivated from most countries, except for those cultivated in the Philippines and Japan. Furthermore, orthogonal projection to latent structure-discriminant analysis provided clear discrimination between rice cultivated in Korea and other countries. The major common variables responsible for differentiation in these models were δ34S, Mn, and Mg. Our findings contribute to understanding the variations of elemental and isotopic compositions in rice depending on geographic origins, and offer valuable insight into the control of fraudulent labeling regarding the geographic origins of rice traded among Asian countries.

Effects of soil type and organic fertilizers on fatty acids and vitamin E in Korean ginseng (Panax ginseng Meyer).

This study examined the effects of soil type and fertilizer regimes on variations in fatty acids (FAs) and vitamin E (Vit-E) in 6-year-old ginseng roots. We observed significant variation in both FA and Vit-E contents owing to the type and quantity of organic fertilizer used in each soil type during cultivation. Unsaturated FAs were approximately 2.7-fold higher in ginseng than in saturated FAs. Linoleic, palmitic, and oleic acids were the most abundant FAs detected in ginseng roots. Additionally, α-tocopherol was the major Vit-E detected. In particular, the increased application of rice straw compost or food waste fertilizer elevated the quantity of nutritionally desirable FAs and bioactive Vit-E in ginseng root. Partial least square-discriminant analysis (PLS-DA) score plots showed that soil type might be the main cause of differences in FA and Vit-E levels in ginseng. Specifically, the PLS-DA model indicated that palmitic acid is a suitable FA marker in determining whether ginseng plants were grown in a paddy-converted field or an upland field. Moreover, linoleic acid levels were highly correlated with α-linolenic acid (r=0.8374; p<0.0001) according to Pearson's correlations and hierarchical clustering analysis. Hence, these preliminary results should prove useful for the reliable production of ginseng containing high phytonutrient quantities according to cultivation conditions.

Next Generation Proteomic Pipeline for Chromosome-Based Proteomic Research Using NeXtProt and GENCODE Databases.

Human Proteome Project aims to map all human proteins including missing proteins as well as proteoforms with post translational modifications, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). neXtProt and Ensemble databases are usually used to provide curated information on human coding genes. However, to find these proteoforms, we (Chr #11 team) first introduce a streamlined pipeline using customized and concatenated neXtProt and GENCODE originated from Ensemble, with controlled false discovery rate (FDR). Because of large sized databases used in this pipeline, we found more stringent FDR filtering (0.1% at the peptide level and 1% at the protein level) to claim novel findings, such as GENCODE ASVs and missing proteins, from human hippocampus data set (MSV000081385) and ProteomeXchange (PXD007166). Using our next generation proteomic pipeline (nextPP) with neXtProt and GENCODE databases, two missing proteins such as activity-regulated cytoskeleton-associated protein (ARC, Chr 8) and glutamate receptor ionotropic, kainite 5 (GRIK5, Chr 19) were additionally identified with two or more unique peptides from human brain tissues. Additionally, by applying the pipeline to human brain related data sets such as cortex (PXD000067 and PXD000561), spinal cord, and fetal brain (PXD000561), seven GENCODE ASVs such as ACTN4-012 (Chr.19), DPYSL2-005 (Chr.8), MPRIP-003 (Chr.17), NCAM1-013 (Chr.11), EPB41L1-017 (Chr.20), AGAP1-004 (Chr.2), and CPNE5-005 (Chr.6) were identified from two or more data sets. The identified peptides of GENCODE ASVs were mapped onto novel exon insertions, alternative translations at 5'-untranslated region, or novel protein coding sequence. Applying the pipeline to male reproductive organ related data sets, 52 GENCODE ASVs were identified from two testis (PXD000561 and PXD002179) and a spermatozoa (PXD003947) data sets. Four out of 52 GENCODE ASVs such as RAB11FIP5-008 (Chr. 2), RP13-347D8.7-001 (Chr. X), PRDX4-002 (Chr. X), and RP11-666A8.13-001 (Chr. 17) were identified in all of the three samples.

Bactericidal activity of cyclotides where phosphatidylethanolamine-lipid selectivity determines antimicrobial spectra.

Cyclotides are a family of plant peptides characterized by a cystine knot embedded in a macrocyclic backbone. They bind to and disrupt phospholipid membranes, which explain their lytic activity on cells. In this study, we expose the full antibacterial potency of cyclotides by avoiding its inhibition by rich growth media assay conditions. For that purpose a two-step microdilution assay protocol was developed, using non-growing conditions during initial peptide incubation. A diverse set of cyclotides was tested for antibacterial and antifungal activity, and the results show that most cyclotides are active under these conditions, especially against Gram-negative bacteria. Activity was observed at sub-micromolar concentrations for three of the cyclotides tested, surpassing that of the control peptides LL-37 and melittin. Noteworthy, two anionic cyclotides were active on Pseudomonas aeruginosa at low micromolar concentrations. Broad-spectrum activity was pronounced among cycloviolacin cyclotides, which included activity on Staphylococcus aureus and Candida albicans. The factors influencing their bactericidal spectrum were revealed by correlating antimicrobial activity with membrane permeabilization on various liposome systems and with the physiochemical properties of the cyclotides. Whereas general electrostatic and hydrophobic parameters are more important for broad-spectrum cyclotides; a phospholipid-specific mechanism of membrane permeabilization, through interaction with phosphatidylethanolamine-lipids, is essential for cyclotides active primarily on Gram-negative bacteria.

Authenticity testing of environment-friendly Korean rice (Oryza sativa L.) using carbon and nitrogen stable isotope ratio analysis.

The increasing demand for organic foods creates, in turn, a pressing need for the development of more accurate tools for the authentication of organic food in order to ensure both fair trade and food safety. This study examines the feasibility of δ13C and δ15N analyses as potential tools for authentication of environment-friendly rice sold in Korea. δ13C and δ15N examination in different rice grains showed that environment-friendly rice can be successfully distinguished from conventional rice. No multi-residue pesticides were detected in the examined rice samples, including conventional rice. This study demonstrates the complementary feasibility of δ13C and δ15N analyses for the authentication of environment-friendly rice sold in Korea in cases where pesticide residue analysis alone is insufficient for discrimination of organic and conventional rice. In future, complementary analyses including compound-specific isotope ratio analysis might be employed for improving the reliability of organic authentication.