Longitudinal observation of tRNA-derived fragments profiles in gestational diabetes mellitus and its diagnostic value.

BACKGROUND: Gestational Diabetes Mellitus (GDM) poses significant risks to maternal and fetal health. Current diagnostic methods based on glucose tolerance tests have limitations for early detection. tRNA-derived small RNAs (tsRNAs) have emerged as potential molecular regulators in various diseases, including metabolic disorders. However, the diagnostic value of tsRNAs in plasma for early GDM or postpartum remains unclear. METHODS: This longitudinal study profiled the expression of tsRNAs across different gestational stages and postpartum in women with GDM (n = 40) and healthy control gestational women (HCs, n = 40). High-throughput small RNA sequencing identified candidate tsRNAs, which were then validated and correlated with clinical biochemical markers such as fasting blood glucose (FBG), HOMA-IR, and GHbA1c. RESULTS: tRF-1:32-Val-AAC-1-M6, tRF-1:31-Glu-CTC-1-M2, and tRF-1:30-Gly-CCC-1-M4 were consistently upregulated in the GDM group compared to HCs during the second trimester (p < 0.05). Only tRF-1:31-Glu-CTC-1-M2 was highly expressed during the first trimester, and tRF-1:30-Gly-CCC-1-M4 increased during postpartum. tRF-1:31-Glu-CTC-1-M2 showed a significant correlation with FBG levels in the first trimester (R = 0.317, p = 0.047). The expression of tRF-1:30-Gly-CCC-1-M4 was significantly correlated with HOMA-IR (r = 0.65, p < 0.001) and GHBA1c (r = 0.33, p = 0.037) during postpartum. A joint diagnostic model incorporating tsRNAs expression and clinical markers demonstrated enhanced predictive power for GDM (ROC AUC = 0.768). CONCLUSION: Our results revealed distinct expression patterns of specific tsRNAs in GDM, showcasing their correlation with key metabolic parameters. This underscores their promising role as biomarkers for early prediction and diagnosis of GDM. The integration of tRFs into a composite biomarker panel holds the potential to improve clinical outcomes by enabling personalized risk assessment and targeted interventions.

Twenty-nine newly sequenced genomes and a comprehensive genome dataset for the insect endosymbiont Buchnera.

Most phloem-feeding insects face nutritional deficiency and rely on their intracellular symbionts to provide nutrients, and most of endosymbiont genomes have undergone reduction. However, the study of genome reduction processes of endosymbionts has been constrained by the limited availability of genome data from different insect lineages. The obligate relationship between aphids and Buchnera aphidicola (hereafter Buchnera) makes them a classic model for studying insect-endosymbiont interaction. Here, we report 29 newly sequenced Buchnera genomes from 11 aphid subfamilies, and a comprehensive dataset based on 90 Buchnera genomes from 14 aphid subfamilies. The dataset shows a significant genomic difference of Buchnera among different aphid lineages. The dataset exhibits a more balanced distribution of Buchnera (from 14 aphid subfamilies) genome sizes, ranging from 400 kb to 600 kb, which can illustrate the genome reduction process of Buchnera. The new genome data provide valuable insights into the microevolutionary processes leading to genomic reduction of insect endosymbionts.

Chromosome-level genome assembly of the cottony cushion scale Icerya purchasi.

The cottony cushion scale, Icerya purchasi, a polyphagous pest, poses a significant threat to the global citrus industry. The hermaphroditic self-fertilization observed in I. purchasi is an exceptionally rare reproductive mode among insects. In this study, we successfully assembled a chromosome-level genome sequence for I. purchasi using PacBio long-reads and the Hi-C technique, resulting in a total size of 1,103.38 Mb and a contig N50 of 12.81 Mb. The genome comprises 14,046 predicted protein-coding genes, with 462,722,633 bp occurrence of repetitive sequences. BUSCO analysis revealed a completeness score of 93.20%. The genome sequence of I. purchasi serves as a crucial resource for comprehending the reproductive modes in insects, with particular emphasis on hermaphroditic self-fertilization.

Enhancing electrochemical water-splitting efficiency with superaerophobic nickel-coated catalysts on Chinese rice paper.

The quest for efficient hydrogen production highlights the need for cost-effective and high-performance catalysts to enhance the electrochemical water-splitting process. A significant challenge in developing self-supporting catalysts lies in the high cost and complex modification of traditional substrates. In this study, we developed catalysts featuring superaerophobic microstructures engineered on microspherical nickel-coated Chinese rice paper (Ni-RP), chosen for its affordability and exceptional ductility. These catalysts, due to their microspherical morphology and textured surface, exhibited significant superaerophobic properties, substantially reducing bubble adhesion. The nickel oxy-hydroxide (NiOxHy) and phosphorus-doped nickel (PNi) catalysts on Ni-RP demonstrated effective roles in oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), achieving overpotentials of 250 mV at 20 mA cm-2 and 87 mV at -10 mA cm-2 in 1 M KOH, respectively. Moreover, a custom water-splitting cell using PNi/Ni-RP and NiOxHy/Ni-RP electrodes reached an impressive average voltage of 1.55 V at 10 mA cm-2, with stable performance over 100 h in 1 M KOH. Our findings present a cost-effective, sustainable, and easily modifiable substrate that utilizes superaerophobic structures to create efficient and durable catalysts for water splitting. This work serves as a compelling example of designing high-performance self-supporting catalysts for electrocatalytic applications.

Photoredox-catalyzed sulfonylation of diaryliodonium salts with DABSO and silyl enolates involving the insertion of SO2.

A versatile photoredox-catalyzed three-component sulfonylation of diaryliodonium salts with DABSO and silyl enolates involving the insertion of SO2 was developed. Moreover, by employing ß-alkyl substituted silyl enolates as substrates, the sulfonylation would give α-alkyl substituted ß-keto sulfones, which are difficult to accessed by previous method involving the insertion of SO2.

The NTE domain of PTENα/ß promotes cancer progression by interacting with WDR5 via its SSSRRSS motif.

PTENα/ß, two variants of PTEN, play a key role in promoting tumor growth by interacting with WDR5 through their N-terminal extensions (NTEs). This interaction facilitates the recruitment of the SET1/MLL methyltransferase complex, resulting in histone H3K4 trimethylation and upregulation of oncogenes such as NOTCH3, which in turn promotes tumor growth. However, the molecular mechanism underlying this interaction has remained elusive. In this study, we determined the first crystal structure of PTENα-NTE in complex with WDR5, which reveals that PTENα utilizes a unique binding motif of a sequence SSSRRSS found in the NTE domain of PTENα/ß to specifically bind to the WIN site of WDR5. Disruption of this interaction significantly impedes cell proliferation and tumor growth, highlighting the potential of the WIN site inhibitors of WDR5 as a way of therapeutic intervention of the PTENα/ß associated cancers. These findings not only shed light on the important role of the PTENα/ß-WDR5 interaction in carcinogenesis, but also present a promising avenue for developing cancer treatments that target this pathway.

Virtual reality treatment could reduce anxiety for women undergoing cesarean section with spinal anesthesia: a randomized controlled trial.

PURPOSE: Cesarean section may result in adverse psychosocial and behavioral outcomes because women put considerable emphasis on the process of birth. Virtual reality treatment has been shown by many studies to reduce anxiety and improve patient satisfaction. Therefore, we designed a randomized controlled trial to investigate whether the application of virtual reality technology during cesarean section can reduce maternal anxiety and improve satisfaction. METHODS: We recruited 128 women undergoing elective cesarean delivery with proposed spinal anesthesia and randomly assigned them to either virtual reality or routine care. The virtual reality intervention was a virtual reality program tailored specifically for women undergoing cesarean section. Primary outcome was the change in anxiety score (change = preoperative-intraoperative score). Secondary outcomes included patient satisfaction score, requirement of intraoperative sedative and analgesic drugs, and respiratory rate. RESULTS: The change in anxiety score in the virtual reality group was significantly higher than that in the routine care group (30 [20, 47.5] vs 10 [- 10, 23.8], respectively; P < 0.001, with Hodges-Lehmann median difference estimate of 20 (95% confidence interval CI, 15-30)). There were no significant differences between the two groups in patient satisfaction scores, the requirement of intraoperative sedative and analgesic drugs, and respiratory rate and side effects. CONCLUSION: Virtual reality treatment could reduce the anxiety of women undergoing elective cesarean section, which is beneficial to the mother and baby. Trial registration This study was registered at the Chinese Clinical Trial Registry (ChiCTR2200061936) on July 11, 2022, and can be reached at https://www.chictr.org.cn/showprojEN.html?proj=173329.

Genetic Causal Relationship Between Alanine Aminotransferase Levels and Risk of Gestational Diabetes Mellitus: Mendelian Randomization Analysis Based on Two Samples.

Gestational diabetes mellitus (GDM) is a frequent complication of pregnancy. The specific mechanisms underlying GDM have not yet been fully elucidated. Contemporary research indicates a potential association between liver enzyme irregularities and an increased risk of metabolic disorders, including diabetes. The alanine aminotransferase (ALT) level is recognized as a sensitive marker of liver injury. An increase in ALT levels is hypothesized to be linked to the pathogenesis of insulin resistance and diabetes. Nonetheless, the definitive causal link between ALT levels and GDM still needs to be determined. This investigation utilized two-sample Mendelian randomization (MR) to examine the genetic causation between alanine aminotransferase (ALT) and GDM. We acquired alanine aminotransferase (ALT)-related GWAS summary data from the UK Biobank, Million Veteran Program, Rotterdam Study, and Lifeline Study. Gestational diabetes data were obtained from the FinnGen Consortium. We employed various MR analysis techniques, including inverse-variance weighted (IVW), MR Egger, weighted median, simple, and weighted weighting. In addition to MR-Egger intercepts, Cochrane's Q test was also used to assess heterogeneity in the MR data, and the MR-PRESSO test was used to assess horizontal pleiotropy. To assess the association's sensitivity, a leave-one-out approach was employed. The IVW results confirmed the independent risk factor for GDM development, as indicated by the ALT level (p = .011). As shown by leave-one-out analysis, horizontal pleiotrophy did not significantly skew the causative link (p > .05). Our dual-sample MR analysis provides substantiated evidence of a genetic causal relationship between alanine aminotransferase (ALT) levels and gestational diabetes.

Seco-cyclic phorbol derivatives and their anti-HIV-1 activities.

Phorbol esters are recognized for their dual role as anti-HIV-1 agents and as activators of protein kinase C (PKC). The efficacy of phorbol esters in binding with PKC is attributed to the presence of oxygen groups at positions C20, C3/C4, and C9 of phorbol. Concurrently, the lipids located at positions C12/C13 are essential for both the anti-HIV-1 activity and the formation of the PKC-ligand complex. The influence of the cyclopropane ring at positions C13 and C14 in phorbol derivatives on their anti-HIV-1 activity requires further exploration. This research entailed the hydrolysis of phorbol, producing seco-cyclic phorbol derivatives. The anti-HIV-1 efficacy of these derivatives was assessed, and the affinity constant (Kd) for PKC-δ protein of selected seco-cyclic phorbol derivatives was determined through isothermal titration calorimetry. The findings suggest that the chemical modification of cyclopropanols could affect both the anti-HIV-1 activity and the PKC binding affinity. Remarkably, compound S11, with an EC50 of 0.27 µmol·L-1 and a CC50 of 153.92 µmol·L-1, demonstrated a potent inhibitory effect on the intermediate products of HIV-1 reverse transcription (ssDNA and 2LTR), likely acting at the viral entry stage, yet showed no affinity for the PKC-δ protein. These results position compound S11 as a potential candidate for further preclinical investigation and for studies aimed at elucidating the pharmacological mechanism underlying its anti-HIV-1 activity.

Symbiotic Bacterial Communities of Insects Feeding on the Same Plant Lineage: Distinct Composition but Congruent Function.

The health and diversity of plant-feeding insects are strictly linked to their host plants and mutualistic symbionts. However, the study of bacterial symbionts within different insects on the same plant lineage is very limited. This study aimed to investigate the bacterial diversity in insect samples that exclusively feed on Bambusa, representing three insect orders, Hemiptera, Lepidoptera, and Blattodea, each exhibiting distinct dietary preferences. The bacterial community was predominantly composed of Proteobacteria, Spirochaetota, Cyanobacteria, Firmicutes, and Bacteroidota. The study found significant variations in symbiotic organisms among three insect orders: hemipterans had Buchnera, lepidopterans had Acinetobacter, and blattodean had Treponema. Furthermore, the dietary preferences of these insects played a pivotal role in shaping the symbiotic relationship of insects. Proteobacteria are prevalent in sap feeders, Spirochaetota dominate in stem feeders, and Cyanobacteria are abundant in leaf feeders. Seasonal influences also affect bacterial symbionts in P. bambucicola, with Serratia present exclusively in winter. We also observed that the bacterial composition varies across all samples, but their core functions appear to be consistent. This highlights the complex relationship between host phylogeny and diet, with phylogeny being the primary driver, shaping adaptations to specialized diets.

Comparison of the efficacy and safety of sodium valproate versus levetiracetam in the treatment of severe traumatic brain injury.

OBJECTIVE: To observe the efficacy and safety of sodium valproate (VPA) compared to levetiracetam (LEV) in the treatment of severe traumatic brain injury (sTBI). METHODS: In this blind, prospective study, eighty-four sTBI patients who had craniotomy from August 2021 to August 2023 were randomly split into two groups through random number table method: LEV and VPA, each with 42 patients. Both received comprehensive treatment post-craniotomy. LEV group: LEV injection on surgery day, transitioning to LEV tablets from day two. VPA group: VPA injection on surgery day, switching to VPA extended-release tablets from day two. The study compared hospital stay, neurological function, clinical outcomes, seizures, and drug reactions between groups. RESULTS: The length of hospital stay showed no significant difference between the LEV and VPA groups. Both groups demonstrated improved neurological function post-treatment (NIHSS and BI scores), with no significant between-group differences. Clinical outcomes at 3 months post-treatment were similar in both groups. Seizure occurrence within 3 months after treatment showed no significant difference between the LEV (19.05%) and VPA (23.81%) groups. However, the VPA group experienced a significantly higher rate of drug-related adverse reactions (40.48%) compared to the LEV group (21.43%). CONCLUSION: Both VPA and LEV are effective in treating sTBI, showing no significant difference in improving neurological function, daily life abilities, treatment outcomes, and seizure occurrence. However, VPA treatment exhibited a significantly higher incidence of drug-related adverse reactions compared to LEV, indicating that LEV might be a safer option for sTBI treatment.

Synthesis and anti-HIV activities of phorbol derivatives.

In this study, 37 derivatives of phorbol esters were synthesized and their anti-HIV-1 activities evaluated, building upon our previous synthesis of 51 phorbol derivatives. 12-Para-electron-acceptor-trans-cinnamoyl-13-decanoyl phorbol derivatives stood out, demonstrating remarkable anti-HIV-1 activities and inhibitory effects on syncytia formation. These derivatives exhibited a higher safety index compared with the positive control drug. Among them, 12-(trans-4-fluorocinnamoyl)-13-decanoyl phorbol, designated as compound 3c, exhibited the most potent anti-HIV-1 activity (EC50 2.9 nmol·L-1, CC50/EC50 11 117.24) and significantly inhibited the formation of syncytium (EC50 7.0 nmol·L-1, CC50/EC50 4891.43). Moreover, compound 3c is hypothesized to act both as an HIV-1 entry inhibitor and as an HIV-1 reverse transcriptase inhibitor. Isothermal titration calorimetry and molecular docking studies indicated that compound 3c may also function as a natural activator of protein kinase C (PKC). Therefore, compound 3c emerges as a potential candidate for developing new anti-HIV drugs.

Correction: Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics.

[This corrects the article DOI: 10.1371/journal.pone.0261768.].

Chemical inhibitors targeting histone methylation readers.

Histone methylation reader domains are protein modules that recognize specific histone methylation marks, such as methylated or unmethylated lysine or arginine residues on histones. These reader proteins play crucial roles in the epigenetic regulation of gene expression, chromatin structure, and DNA damage repair. Dysregulation of these proteins has been linked to various diseases, including cancer, neurodegenerative diseases, and developmental disorders. Therefore, targeting these proteins with chemical inhibitors has emerged as an attractive approach for therapeutic intervention, and significant progress has been made in this area. In this review, we will summarize the development of inhibitors targeting histone methylation readers, including MBT domains, chromodomains, Tudor domains, PWWP domains, PHD fingers, and WD40 repeat domains. For each domain, we will briefly discuss its identification and biological/biochemical functions, and then focus on the discovery of inhibitors tailored to target this domain, summarizing the property and potential application of most inhibitors. We will also discuss the structural basis for the potency and selectivity of these inhibitors, which will aid in further lead generation and optimization. Finally, we will also address the challenges and strategies involved in the development of these inhibitors. It should facilitate the rational design and development of novel chemical scaffolds and new targeting strategies for histone methylation reader domains with the help of this body of data.

Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review.

INTRODUCTION: Patient-reported outcomes (PROs; symptoms, functional status, quality-of-life) expressed in the 'free-text' or 'unstructured' format within clinical notes from electronic health records (EHRs) offer valuable insights beyond biological and clinical data for medical decision-making. However, a comprehensive assessment of utilizing natural language processing (NLP) coupled with machine learning (ML) methods to analyze unstructured PROs and their clinical implementation for individuals affected by cancer remains lacking. AREAS COVERED: This study aimed to systematically review published studies that used NLP techniques to extract and analyze PROs in clinical narratives from EHRs for cancer populations. We examined the types of NLP (with and without ML) techniques and platforms for data processing, analysis, and clinical applications. EXPERT OPINION: Utilizing NLP methods offers a valuable approach for processing and analyzing unstructured PROs among cancer patients and survivors. These techniques encompass a broad range of applications, such as extracting or recognizing PROs, categorizing, characterizing, or grouping PROs, predicting or stratifying risk for unfavorable clinical results, and evaluating connections between PROs and adverse clinical outcomes. The employment of NLP techniques is advantageous in converting substantial volumes of unstructured PRO data within EHRs into practical clinical utilities for individuals with cancer.

Partial Correspondence between Host Plant-Related Differentiation and Symbiotic Bacterial Community in a Polyphagous Insect.

Host plants play a vital role in insect population differentiation, while symbiotic associations between bacteria and insects are ubiquitous in nature. However, existing studies have given limited attention to the connection between host-related differentiation and symbiotic bacterial communities in phytophagous insects. In this study, we collected 58 samples of Aphis odinae from different host plants in southern China and constructed phylogenetic trees to investigate their differentiation in relation to host plants. We also selected aphid samples from the five most preferred host plants and analyzed their symbiotic bacterial composition using Illumina sequencing of the V3-V4 hypervariable region of the 16S rRNA gene. The phylogeny and symbiotic bacterial community structure of A. odinae populations on different host plants showed that samples from Triadica sebifera (Euphorbiaceae) had a consistent presence of Wolbachia as the predominant secondary symbiont and suggested the possibility of undergoing differentiation. Conversely, although differentiation was observed in samples from Rhus chinensis (Anacardiaceae), no consistent presence of predominant secondary symbionts was found. Additionally, the samples from Heptapleurum heptaphyllum (Araliaceae) consistently carried Serratia, but no host differentiation was evident. In summary, this study reveals a partial correspondence between symbiotic bacterial communities and host-related differentiation in A. odinae. The findings contribute to our understanding of the microevolutionary influencing the macroevolutionary relationships between bacterial symbionts and phytophagous insects. The identification of specific symbionts associated with host-related differentiation provides valuable insights into the intricate dynamics of insect-bacteria interactions.

Palladium-Catalyzed C2-Selective Direct Arylation of Benzo[b]thiophene 1,1-Dioxides with Arylboronic Acids.

A novel oxidative cross-coupling of benzo[b]thiophene 1,1-dioxides with arylboronic acids was reported. The efficient reaction occurred at the C2-position via C-H activation, followed by Pd(II)-catalyzed arylation. Furthermore, a series of C2-arylated products with significant photoluminescence properties have been synthesized and characterized, which illustrates the potential applications of our method in the aggregation-induced emission field.

Innovative accumulative risk assessment of co-exposure to Cd, As, and Pb in contaminated rice based on their in vivo bioavailability and in vitro bioaccessibility.

The consumption of cadmium (Cd), arsenic (As), and lead (Pb) co-contaminated rice exposes humans to multiple heavy metals simultaneously, with relative bioavailability (RBA) and bioaccessibility (BAc) being important determinants of potential health risks. This study evaluated the relationship between in vivo RBA and in vitro BAc of Cd, As, and Pb in rice and their cumulative risk to humans. A total of 110 rice samples were collected in Zhejiang Province, China, and 10 subsamples with varying concentration gradients were randomly selected to measure RBA using a mouse model (liver, kidney, femur, blood, and urine as endpoints) and BAc using four in vitro assays (PBET, UBM, SBRC, and IVG). Our results indicated that Cd-RBA varied from 21.2 % to 67.5 %, As-RBA varied from 23.2 % to 69.3 %, and Pb-RBA varied from 22.2 % to 68.9 % based on mouse liver plus kidneys. The BAc values for Cd, As, and Pb in rice varied according to the assay. Compared to Cd and As, Pb exhibited a lower BAc in the gastric (GP) and intestinal (IP) phases. According to the relationship between the BAc and RBA values, IVG-GP (R2 = 0.92), SBRC-IP (R2 = 0.73), and UBM-GP (R2 = 0.80) could be used as predictors of Cd-, As-, and Pb-RBA in rice, respectively. The health risks associated with co-exposure to Cd, As, and Pb in contaminated rice for both adults and children exceeded the acceptable threshold, with Cd and As being the primary risk factors. The noncarcinogenic and carcinogenic risks were markedly reduced when the RBA and BAc values were incorporated into the risk assessment. Due to the risk overestimation inherent in estimating the risk level based on total metal concentration, our study provides a realistic assessment of the cumulative health risks associated with co-exposure to Cd, As, and Pb in contaminated rice using in vivo RBA and in vitro BAc bioassays.

Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review.

OBJECTIVE: Natural language processing (NLP) combined with machine learning (ML) techniques are increasingly used to process unstructured/free-text patient-reported outcome (PRO) data available in electronic health records (EHRs). This systematic review summarizes the literature reporting NLP/ML systems/toolkits for analyzing PROs in clinical narratives of EHRs and discusses the future directions for the application of this modality in clinical care. METHODS: We searched PubMed, Scopus, and Web of Science for studies written in English between 1/1/2000 and 12/31/2020. Seventy-nine studies meeting the eligibility criteria were included. We abstracted and summarized information related to the study purpose, patient population, type/source/amount of unstructured PRO data, linguistic features, and NLP systems/toolkits for processing unstructured PROs in EHRs. RESULTS: Most of the studies used NLP/ML techniques to extract PROs from clinical narratives (n = 74) and mapped the extracted PROs into specific PRO domains for phenotyping or clustering purposes (n = 26). Some studies used NLP/ML to process PROs for predicting disease progression or onset of adverse events (n = 22) or developing/validating NLP/ML pipelines for analyzing unstructured PROs (n = 19). Studies used different linguistic features, including lexical, syntactic, semantic, and contextual features, to process unstructured PROs. Among the 25 NLP systems/toolkits we identified, 15 used rule-based NLP, 6 used hybrid NLP, and 4 used non-neural ML algorithms embedded in NLP. CONCLUSIONS: This study supports the potential utility of different NLP/ML techniques in processing unstructured PROs available in EHRs for clinical care. Though using annotation rules for NLP/ML to analyze unstructured PROs is dominant, deploying novel neural ML-based methods is warranted.

Graphidessajinfoensis, a new species of longhorned beetle (Coleoptera, Cerambycidae, Lamiinae, Desmiphorini) from China.

Graphidessajinfoensissp. nov. is described from Chongqing and Guizhou in Southwest China. The diagnostic morphological characters of the new species are described and illustrated in color plates. The distribution of all species of the genus Graphidessa Bates, 1884 is mapped and the key to all species of this genus is updated. The COI gene sequence of the new species is also provided.