Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic Peptides.

Animal venoms, distinguished by their unique structural features and potent bioactivities, represent a vast and relatively untapped reservoir of therapeutic molecules. However, limitations associated with extracting or expressing large numbers of individual venoms and venom-like molecules have precluded their therapeutic evaluation via high throughput screening. Here, we developed an innovative computational approach to design a highly diverse library of animal venoms and "metavenoms". We employed programmable M13 hyperphage display to preserve critical disulfide-bonded structures for highly parallelized single-round biopanning with quantitation via high-throughput DNA sequencing. Our approach led to the discovery of Kunitz type domain containing proteins that target the human itch receptor Mas-related G protein-coupled receptor X4 (MRGPRX4), which plays a crucial role in itch perception. Deep learning-based structural homology mining identified two endogenous human homologs, tissue factor pathway inhibitor (TFPI) and serine peptidase inhibitor, Kunitz type 2 (SPINT2), which exhibit agonist-dependent potentiation of MRGPRX4. Highly multiplexed screening of animal venoms and metavenoms is therefore a promising approach to uncover new drug candidates.

Cardiovascular risk in chronic hepatitis B patients treated with tenofovir disoproxil fumarate or tenofovir alafenamide

Background/Aims@#Tenofovir disoproxil fumarate (TDF) is known to have a lipid-lowering effect. This is in contrast to tenofovir alafenamide (TAF), which has a lipid-neutral effect. Therefore, concerns have been raised as to whether these differences affect long-term cardiovascular risk. Here, we aimed to evaluate the long-term risk of cardiovascular events in chronic hepatitis B (CHB) patients treated with TAF or TDF. @*Methods@#We retrospectively analyzed 4,124 treatment-naïve CHB patients treated with TDF (n=3,186) or TAF (n=938) between 2012 and 2022. The primary outcome was a composite endpoint of major adverse cardiovascular events (MACE), including myocardial infarction, ischemic stroke, and hospitalization for unstable angina or heart failure. Serial changes in lipid profiles between two treatments were also explored. @*Results@#The median age of the patients was 50.6 years, and 60.6% of the patients were male. At baseline, 486 (11.8%) and 637 (15.4%) of the patients had dyslipidemia and fatty liver, respectively. A total of 42 MACE occurred, with an annual incidence of 0.2%/100 person-years (PYs). At 1, 3, and 5 years, the cumulative risk of MACE was 0.4%, 0.8%, and 1.2% in patients treated with TDF, and 0.2%, 0.7%, and 0.7% in patients treated with TAF, respectively (p=0.538). No significant differences in the risk of MACE were observed between TDF and TAF. A multivariable analysis found that current smoker and a history of cardiovascular events were risk factors associated with an increased risk of MACE. @*Conclusions@#Patients treated with TAF had comparable risks of cardiovascular outcomes, defined as MACE, as patients treated with TDF.

Prediction of Hepatocellular Carcinoma Development in Korean Patients after Hepatitis C Cure with Direct-Acting Antivirals

Background/Aims@#With the wide application of direct-acting antivirals (DAAs) for hepatitis C virus infection, the number of patients achieving a sustained virologic response (SVR) will continue to increase. However, no consensus has been achieved on exempting SVR-achieving patients from hepatocellular carcinoma (HCC) surveillance. @*Methods@#Between 2013 and 2021, 873 Korean patients who achieved SVR following DAA treatment were analyzed. We evaluated the predictive performance of seven noninvasive scores (PAGE-B, modified PAGE-B, Toronto HCC risk index, fibrosis-4, aspartate aminotransferase-toplatelet ratio index, albumin-bilirubin, and age male albumin-bilirubin platelet [aMAP]) at baseline and after SVR. @*Results@#The mean age of the 873 patients (39.3% males) was 59.1 years, and 224 patients (25.7%) had cirrhosis. During 3,542 person-years of follow-up, 44 patients developed HCC, with an annual incidence of 1.24/100 person-years. Male sex (adjusted hazard ratio [AHR], 2.21), cirrhosis (AHR, 7.93), and older age (AHR, 1.05) were associated with a significantly higher HCC risk in multivariate analysis. The performance of all scores at the time of SVR were numerically better than those at baseline as determined by the integrated area under the curve. Timedependent area under the curves for predicting the 3-, 5-, and 7-year risk of HCC after SVR were higher in mPAGE-B (0.778, 0.746, and 0.812, respectively) and aMAP (0.776, 0.747, and 0.790, respectively) systems than others. No patients predicted as low-risk by the aMAP or mPAGE-B systems developed HCC. @*Conclusions@#aMAP and mPAGE-B scores demonstrated the highest predictive performance for de novo HCC in DAA-treated, SVR-achieving patients. Hence, these two systems may be used to identify low-risk patients that can be exempted from HCC surveillance.

Flexible protein-protein docking with a multitrack iterative transformer.

Conventional protein-protein docking algorithms usually rely on heavy candidate sampling and reranking, but these steps are time-consuming and hinder applications that require high-throughput complex structure prediction, for example, structure-based virtual screening. Existing deep learning methods for protein-protein docking, despite being much faster, suffer from low docking success rates. In addition, they simplify the problem to assume no conformational changes within any protein upon binding (rigid docking). This assumption precludes applications when binding-induced conformational changes play a role, such as allosteric inhibition or docking from uncertain unbound model structures. To address these limitations, we present GeoDock, a multitrack iterative transformer network to predict a docked structure from separate docking partners. Unlike deep learning models for protein structure prediction that input multiple sequence alignments, GeoDock inputs just the sequences and structures of the docking partners, which suits the tasks when the individual structures are given. GeoDock is flexible at the protein residue level, allowing the prediction of conformational changes upon binding. On the Database of Interacting Protein Structures (DIPS) test set, GeoDock achieves a 43% top-1 success rate, outperforming all other tested methods. However, in the standard DIPS train/test splits, we discovered contamination of close homologs in the training set. After decontaminating the training set, the success rate is 31%. On the DB5.5 test set and a benchmark dataset of antibody-antigen complexes, GeoDock outperforms the deep learning models trained using the same dataset but falls behind most of the conventional methods and AlphaFold-Multimer. GeoDock attains an average inference speed of under 1 s on a single GPU, enabling its application in large-scale structure screening. Although binding-induced conformational changes are still a challenge owing to limited training and evaluation data, our architecture sets up the foundation to capture this backbone flexibility. Code and a demonstration Jupyter notebook are available at https://github.com/Graylab/GeoDock.

Can perioperative electroencephalogram and adverse hemodynamic events predict neurodevelopmental outcomes in infants with congenital heart disease?

OBJECTIVE: The study objective was to characterize preoperative and postoperative continuous electroencephalogram metrics and hemodynamic adverse events as predictors of neurodevelopment in congenital heart disease infants undergoing cardiac surgery. METHODS: From 2010 to 2021, 320 infants underwent congenital heart disease surgery at our institution, of whom 217 had perioperative continuous electroencephalogram monitoring and were included in our study. Neurodevelopment was assessed in 76 patients by the Bayley Scales of Infant and Toddler Development, 3rd edition, consisting of cognitive, communication, and motor scaled scores. Patient and procedural factors, including hemodynamic adverse events, were included by means of the likelihood of covariate selection in our predictive model. Median (25th, 75th percentile) follow-up was 1.03 (0.09, 3.44) years with 3 (1, 6) Bayley Scales of Infant and Toddler Development, 3rd Edition evaluations per patient. RESULTS: Median age at index surgery was 7 (4, 23) days, and 81 (37%) were female. Epileptiform discharges, encephalopathy, and abnormality (lethargy and coma) were more prevalent on postoperative continuous electroencephalograms, compared with preoperative continuous electroencephalograms (P < .005). In 76 patients with Bayley Scales of Infant and Toddler Development, 3rd edition evaluations, patients with diffuse abnormality (P = .009), waveform discontinuity (P = .007), and lack of continuity (P = .037) on preoperative continuous electroencephalogram had lower cognitive scores. Patients with synchrony (P < .005) on preoperative and waveform continuity (P = .009) on postoperative continuous electroencephalogram had higher fine motor scores. Patients with postoperative adverse events had lower cognitive (P < .005) and gross motor scores (P < .005). CONCLUSIONS: Phenotypic patterns of perioperative continuous electroencephalogram metrics are associated with late-term neurologic injury in infants with congenital heart disease requiring surgery. Continuous electroencephalogram metrics can be integrated with hemodynamic adverse events in a predictive algorithm for neurologic impairment.

Discussion on the Differences in Aroma Components in Different Fragrant Rice Varieties during Storage.

Rice (Oryza sativa L.) is an important food crop in Taiwan, among which fragrant rice is highly regarded for its special aroma when cooked. During the storage of fragrant rice, the aroma components will change, which will affect the aroma quality of fragrant rice. Therefore, headspace solid-phase microextraction (HS-SPME) was used in this study, combined with gas chromatography and gas chromatography-mass spectrometry, to analyze the difference in the aroma components of Taikeng No. 4 (TK4), Tainung No. 71 (TN71), Kaohsiung No. 147 (KH147), and Taichung No. 194 (TC194) fragrant rice. A total of 28 aroma components were identified in the four varieties of fragrant rice, and the main components were all Nonanal. Among them, TK4 contains a very high content of hydrocarbons, including Tridecane and Dodecane; TN71, KH147, and TC194 contain mainly aldehydes such as Nonanal and Hexanal. During different storage times, the contents of alcohols, monoterpenes, aromatic aldehydes, and furans increased with storage time, while the content of aliphatic aldehydes decreased with storage time. After storage, the fragrant rice samples showed a tendency for the total volatile component content to decrease, with the most pronounced reduction observed in Nonanal content.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Single cohesin molecules generate force by two distinct mechanisms.

Spatial organization of DNA is facilitated by cohesin protein complexes that move on DNA and extrude DNA loops. How cohesin works mechanistically as a molecular machine is poorly understood. Here, we measure mechanical forces generated by conformational changes in single cohesin molecules. We show that bending of SMC coiled coils is driven by random thermal fluctuations leading to a ~32 nm head-hinge displacement that resists forces up to 1 pN; ATPase head engagement occurs in a single step of ~10 nm and is driven by an ATP dependent head-head movement, resisting forces up to 15 pN. Our molecular dynamic simulations show that the energy of head engagement can be stored in a mechanically strained conformation of NIPBL and released during disengagement. These findings reveal how single cohesin molecules generate force by two distinct mechanisms. We present a model, which proposes how this ability may power different aspects of cohesin-DNA interaction.

Flexible Protein-Protein Docking with a Multi-Track Iterative Transformer.

Conventional protein-protein docking algorithms usually rely on heavy candidate sampling and re-ranking, but these steps are time-consuming and hinder applications that require high-throughput complex structure prediction, e.g., structure-based virtual screening. Existing deep learning methods for protein-protein docking, despite being much faster, suffer from low docking success rates. In addition, they simplify the problem to assume no conformational changes within any protein upon binding (rigid docking). This assumption precludes applications when binding-induced conformational changes play a role, such as allosteric inhibition or docking from uncertain unbound model structures. To address these limitations, we present GeoDock, a multi-track iterative transformer network to predict a docked structure from separate docking partners. Unlike deep learning models for protein structure prediction that input multiple sequence alignments (MSAs), GeoDock inputs just the sequences and structures of the docking partners, which suits the tasks when the individual structures are given. GeoDock is flexible at the protein residue level, allowing the prediction of conformational changes upon binding. For a benchmark set of rigid targets, GeoDock obtains a 41% success rate, outperforming all the other tested methods. For a more challenging benchmark set of flexible targets, GeoDock achieves a similar number of top-model successes as the traditional method ClusPro [1], but fewer than ReplicaDock2 [2]. GeoDock attains an average inference speed of under one second on a single GPU, enabling its application in large-scale structure screening. Although binding-induced conformational changes are still a challenge owing to limited training and evaluation data, our architecture sets up the foundation to capture this backbone flexibility. Code and a demonstration Jupyter notebook are available at https://github.com/Graylab/GeoDock.

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.

Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic recombination and mutation. Even with recent advances, accurate structural prediction of these loops remains a challenge. Here, we present IgFold, a fast deep learning method for antibody structure prediction. IgFold consists of a pre-trained language model trained on 558 million natural antibody sequences followed by graph networks that directly predict backbone atom coordinates. IgFold predicts structures of similar or better quality than alternative methods (including AlphaFold) in significantly less time (under 25 s). Accurate structure prediction on this timescale makes possible avenues of investigation that were previously infeasible. As a demonstration of IgFold's capabilities, we predicted structures for 1.4 million paired antibody sequences, providing structural insights to 500-fold more antibodies than have experimentally determined structures.

Preliminary study on the application of bioimpedance analysis to measure the psoas major muscle in older adults.

For the assessment of sarcopenia or other geriatric frailty syndromes, psoas major area may be one of the primary indicators. Aim to develop and cross-validate the psoas cross-sectional area estimation equation of L3-L4 of the elderly over 60 years old by bioelectrical impedance analysis (BIA). Ninety-two older adults with normal mobility were enrolled (47 females, 45 males), and were randomly divided into a modeling group (MG, n = 62) and validation group (VG, n = 30). Computed tomography (CT) was used to measure the psoas major area at the' L3-L4 lumbar vertebrae height as a predictor. Estimated variables were height (h), whole body impedance (Zwhole), whole body impedance index (h2/Zwhole, WBI), age, gender (female = 0, male = 1), and body weight (weight) by standing BIA. Relevant variables were estimated using stepwise regression analysis. Model performance was confirmed by cross-validation. BIA estimation equation for PMM obtained from the MG was: (PMMBIA = 0.183 h2/Z- 0.223 age + 4.443 gender + 5.727, r2 = 0.702, n = 62, SEE = 2.432 cm2, p < 0.001). The correlation coefficient r obtained by incorporating the VG data into the PMM equation was 0.846, and the LOA ranged from -4.55 to 4.75 cm2. PMMBIA and PMMCT both correlate highly with MG or VG with small LOA. The fast and convenient standing BIA for measuring PMM may be a promising method that is worth developing.

WT1 regulates expression of DNA repair gene Neil3 during nephrogenesis.

Mammalian nephrons arise from a population of nephron progenitor cells (NPCs) expressing the master transcription factor Wilms tumor-1 (WT1), which is crucial for NPC proliferation, migration, and differentiation. In humans, biallelic loss of WT1 precludes nephrogenesis and leads to the formation of Wilms tumor precursor lesions. We hypothesize that WT1 normally primes the NPC for nephrogenesis by inducing expression of NPC-specific DNA repair genes that protect the genome. We analyzed transcript levels for a panel of DNA repair genes in embryonic day 17.5 (E17.5) versus adult mouse kidneys and noted seven genes that were increased >20-fold. We then isolated Cited1+ NPCs from E17.5 kidneys and found that only one gene, nei-like DNA glycosylase 3 (Neil3), was enriched. RNAscope in situ hybridization of E17.5 mouse kidneys showed increased Neil3 expression in the nephrogenic zone versus mature nephron structures. To determine whether Neil3 expression is WT1 dependent, we knocked down Wt1 in Cited1+ NPCs (60% knockdown efficiency) and noted a 58% reduction in Neil3 transcript levels. We showed that WT1 interacts with the Neil3 promoter and that activity of a Neil3 promoter-reporter vector was increased twofold in WT1+ versus WT1- cells. We propose that Neil3 is a WT1-dependent DNA repair gene expressed at high levels in Cited1+ NPCs, where it repairs mutational injury to the genome during nephrogenesis. NEIL3 is likely just one of many such lineage-specific repair mechanisms that respond to genomic injury during kidney development.NEW & NOTEWORTHY We studied the molecular events leading to Wilms tumors as a model for the repair of genomic injury. Specifically, we showed that WT1 activates DNA repair gene Neil3 in nephron progenitor cells. However, our observations offer a much broader principle, demonstrating that the embryonic kidney invests in lineage-specific expression of DNA repair enzymes. Thus, it is conceivable that failure of these mechanisms could lead to a variety of "sporadic" congenital renal malformations and human disease.

End of induction patient reported outcomes predict clinical remission and endoscopic improvement with vedolizumab and adalimumab in ulcerative colitis.

BACKGROUND: Patient-reported outcomes (PROs) are increasingly emphasized as endpoints in clinical trials of ulcerative colitis (UC). However, the prognostic value of early improvement in PROs for long-term outcomes remains unclear. METHODS: This was a post-hoc analysis of 611 vedolizumab-treated or adalimumab-treated patients in the VARSITY trial (Clinicaltrial.gov: NCT02497469). Stool frequency (SF) and rectal bleeding score (RBS) as reported in the Mayo score at post-induction (week 6 and 14) was assessed for their association with one-year endoscopic improvement (EI), defined as Mayo endoscopic subscore <2; histo-endoscopic mucosal improvement (HEMI), defined as EI and Geboes highest grade <3.2, clinical remission (CR), defined as total Mayo score ≤2; and PRO-2 remission, defined as RBS of 0 and SF ≤1. Multivariable logistic regression models adjusted for confounders assessed the relationships between post-induction PROs and outcomes of interest at one-year. RESULTS: Patients with severe SF at week 6 were significantly less likely to achieve one-year EI compared to those with non-severe SF [aOR 0.40 (95% CI: 0.24-0.68), p < .001]. Absence of rectal bleeding at week 6 was associated with greater odds of achieving EI at one-year [aOR 2.21 (95% CI: 1.58-3.09), p < .001]. These findings were consistent across comparisons at week 14. Similar findings were observed for the outcomes of one-year HEMI, CR and PRO-2 remission. No difference was observed between the modified partial Mayo score and modified PRO-2 score. CONCLUSIONS: Post-induction PROs strongly predict the odds of CR and EI in UC and simplified evaluations can be used to assess early response to UC therapies.

Subclassification of advanced-stage hepatocellular carcinoma with macrovascular invasion: combined transarterial chemoembolization and radiotherapy as an alternative first-line treatment

Background@#/Aim: The Barcelona Clinic Liver Cancer (BCLC) guidelines recommend systemic therapy as the only first-line treatment for patients with BCLC stage C hepatocellular carcinoma (HCC) despite its heterogeneity of disease extent. We aimed to identify patients who might benefit from combined transarterial chemoembolization (TACE) and radiation therapy (RT) by subclassifying BCLC stage C. @*Methods@#A total of 1,419 treatment-naïve BCLC stage C patients with macrovascular invasion (MVI) who were treated with combined TACE and RT (n=1,115) or systemic treatment (n=304) were analyzed. The primary outcome was overall survival (OS). Factors associated with OS were identified and assigned points by the Cox model. The patients were subclassified into three groups based on these points. @*Results@#The mean age was 55.4 years, and 87.8% were male. The median OS was 8.3 months. Multivariate analysis revealed a significant association of Child-Pugh B, infiltrative-type tumor or tumor size ≥10 cm, main or bilateral portal vein invasion, and extrahepatic metastasis with poor OS. The sub-classification was categorized into low (point ≤1), intermediate (point=2), and high (point ≥3) risks based on the sum of points (range, 0–4). The OS in the low, intermediate, and high-risk groups was 22.6, 8.2, and 3.8 months, respectively. In the low and intermediate-risk groups, patients treated with combined TACE and RT exhibited significantly longer OS (24.2 and 9.5 months, respectively) than those who received systemic treatment (6.4 and 5.1 months, respectively; P<0.0001). @*Conclusions@#Combined TACE and RT may be considered as a first-line treatment option for HCC patients with MVI when classified into low- and intermediate-risk groups.

Analysis of Volatile Compounds from Different Parts of Houttuynia cordata Thunb.

Houttuynia cordata Thunb. is a medicinal and edible plant that has been commonly used in traditional Chinese medicine since ancient times. This study used headspace solid-phase microextraction (HS-SPME) and direct injection, combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS), to identify the volatile compounds in H. cordata. Extraction from different parts of the plant using different extraction techniques for the identification of volatile compounds were determined. A total of 93 volatile components were analyzed in the leaves, stems, rhizomes, and whole plant samples of H. cordata. The leaves contained more (Z)-3-hexenal, ß-myrcene, (Z)-ß-ocimene, and (4E,6E)-allo-ocimene; the stems contained more geranyl acetate and nerolidol; and rhizomes contained more α-pinene, ß-pinene, limonene, 2-undecanone, and decanoyl acetaldehyde. Among them, the essential oil extracted by HS-SPME could produce more monoterpenes, while direct injection could obtain higher contents of aliphatic ketones, terpene esters, sesquiterpenes, and was more conducive to the extraction of 2-undecanone and decanoyl acetaldehyde.

Chemical Properties of Peanut Oil from Arachis hypogaea L. 'Tainan 14' and Its Oxidized Volatile Formation.

Arachis hypogaea L. 'Tainan 14' has purple skin characteristics. This study investigated the effects of different materials (shelled or unshelled peanuts) and temperatures (120 or 140 °C) on the properties of extracted peanut oil. The results show that its antioxidant components (total flavonoid, α−tocopherol, and γ-tocopherol) and oxidative stability were mainly affected by the roasting temperature (p < 0.05). Fifty-eight volatile compounds were identified by peanut oil oxidation and divided into three main groups during the roasting process using principal component analysis. The volatile formation changes of different materials and temperatures were assessed by agglomerative hierarchical clustering analysis. These results provide useful reference information for peanut oil applications in the food industry.

Acute Effects of Static Stretching Combined with Vibration and Nonvibration Foam Rolling on the Cardiovascular Responses and Functional Fitness of Older Women with Prehypertension.

We compared the effects of three warm-up protocols (static stretching (SS), static stretching with vibration foam rolling (SS + VFR), and static stretching with nonvibration foam rolling (SS + FR) on the blood pressure and functional fitness performance in older women with prehypertension. Thirteen older women went through different protocols in separate visits, and their systolic (SBP) and diastolic (DBP) blood pressure, heart rate, mean arterial pressure, brachial pulse pressure (BPP), functional fitness test (back scratch (BS), chair-sit-and-reach, 30 s arm curl (AC), 30 s chair stand, 2 min step, 8-foot up and go), and single-leg standing balance (SLB) were recorded. The SBP and BPP were significantly higher after SS and SS + VFR than after SS + FR. Both SS + FR and SS + VFR significantly improved the 2 min step, when compared with SS. Additionally, SS + VFR significantly improved the BS and AC performance. However, compared with SS and SS + FR, SS + VFR significantly reduced the SLB performance. Therefore, SS + FR may be a better warm-up protocol for older women in maintaining blood pressure. On the other hand, even though SS + VFR induced superior shoulder flexibility, aerobic endurance, and arm strength, it could impair balance.

Bioimpedance analysis combined with sagittal abdominal diameter for abdominal subcutaneous fat measurement.

Abdominal subcutaneous fat tissue (ASFT) is an independent predictor of mortality. This prospective observational study aimed to establish a rapid, safe, and convenient estimation equation for abdominal subcutaneous fat area (SFA) using bioimpedance analysis (BIA) combined with sagittal abdominal diameter (SAD). A total of 520 adult subjects were recruited and were randomly divided into 2/3 (n = 346) and 1/3 (n = 174) to form a modeling group (MG) and a validation group (VG), respectively. Each subject's abdomen was scanned using computed tomography to obtain target variables (SFACT). Predictor variables for all subjects included bioimpedance index (h2/Z), anthropometric parameters height (h), weight (W), waist circumference (WC), hip circumference (HC), and SAD, along with age and sex (male =1, female = 0). SFA estimation equation SFABIA+SAD was established for the MG using stepwise multiple regression analysis. Cross-validation was performed using VG to evaluate the performance of the SFABIA+SAD estimation equation. Stepwise multiple regression analysis was applied from the MG, including SFABIA+SAD = 49.89 + 1.09 SAD-29.90 Sex + 4.71 W-3.63 h2/Z-1.50 h (r = 0.92, SEE = 28.10 cm2, n = 346, p < 0.001). Mean differences in SFABIA+SAD relative to SFACT were -1.21 ± 21.53, 2.85 ± 27.16, and -0.98 ± 36.6 cm2 at different levels of obesity (eutrophic, overweight, obese), respectively. This study did not have a large number of samples in different fields, so it did not have completely external validity. Application of BIA combined with SAD in anthropometric parameters achieves fast, accurate and convenient SAF measurement. Results of this study provide a simple, reliable, and practical measurement that can be widely used in epidemiological studies and in measuring individual SFA.

Effects of Different Extraction Methods on Vanilla Aroma.

To establish the analytic conditions for examining the aroma quality of vanilla pods, we compared different extraction methods and identified a suitable option. We utilized headspace solid-phase microextraction (HS-SPME), steam distillation (SD), simultaneous steam distillation (SDE) and alcoholic extraction combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) to identify volatile components of vanilla pods. A total of 84 volatile compounds were identified in this experiment, of which SDE could identify the most volatile compounds, with a total of 51 species, followed by HS-SPME, with a total of 28 species. Ten volatile compounds were identified by extraction with a minimum of 35% alcohol. HS-SPME extraction provided the highest total aroma peak areas, and the peak areas of aldehydes, furans, alcohols, monoterpenes and phenols compounds were several times higher than those of the other extraction methods. The results showed that the two technologies, SDE and HS-SPME, could be used together to facilitate analysis of vanilla pod aroma.

Long-term effect of plastic feeding on growth and transcriptomic response of mealworms (Tenebrio molitor L.).

Plastic waste has been considered a serious global environmental problem for decades. Despite the high recalcitrance of synthetic plastics, the biodegradation of polyethylene (PE), polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC) by some insect larvae has been reported; however, the mechanism of degradation remains largely unknown. We investigated the effects of plastics on the growth of mealworms (larvae of Tenebrio molitor) and their role in PS and PE degradation. Mealworms were capable of ingesting high-impact polystyrene (HIPS), expanded polystyrene (EPS) and low-density polyethylene (LDPE) but not linear low-density polyethylene (LLDPE) or polypropylene (PP). Plastic consumption was negatively dependent on plastic crystallinity. Transcriptome analysis and KEGG mapping revealed that mealworms act as downstream decomposers in plastic depolymerization and that fatty acid degradation pathways may play important roles in the digestion of plastic degradation intermediates produced by gut bacteria. In addition, PS and PE degradation was achieved via the diffusion of extracellular depolymerases, which probably acted on the distal backbone and produce shorter linear chains that containing ≤16 C atoms instead of branched chains. Additionally, the intermediates of PS degradation are expected to be further decomposed by mealworms as xenobiotics. This study provided a preliminary understanding of plastic degradation mechanism by mealworms.