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The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy generation. To achieve safe management and optimal control of batteries, the state of charge (SOC) is one of the important parameters. The machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent years. However, a common problem with these models is that their estimation performances are not always stable, which makes them difficult to use in practical applications. To address this problem, an optimized radial basis function neural network (RBF-NN) that combines the concepts of Golden Section Method (GSM) and Sparrow Search Algorithm (SSA) is proposed in this paper. Specifically, GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model, and its parameters such as radial base center, connection weights and so on are optimized by SSA, which greatly improve the performance of RBF-NN in SOC estimation. In the experiments, data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model, and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.

Abstract Background Hem-o-Lok clips (HOLCs) are widely used in minimal access urological operations due to the advantage of vascular control and suture stabilization. In rare cases, however, they can develop problems themselves. Migration of HOLCs into the collecting system is a fairly rare complication after laparoscopic pyelolithotomy. To date, only two cases were reported in the literature. Case presentation This article describes a case of 51-year-old man with a complaint of left flank pain. He had a medical history of ipsilateral retroperitoneal laparoscopic pyelolithotomy at another hospital 8 years ago. Non-contrast CT scan demonstrated a renal stone in the left ureteropelvic junction complicated by mild hydronephrosis. A straight foreign body was found near the renal pelvis, with part of it wedging into renal pelvic wall. A percutaneous nephrolithotomy (PNL) was performed for this patient. After some fragmentation, a HOLC was found in the kernel of the stone. With an alligator plier, the clip was totally removed out of the collecting system. The postoperative period and follow-up were uneventful. Conclusions HOLC migration into renal pelvis is a rare complication following laparoscopic pyelolithotomy. It could act as nidus for stone formation under extended exposure to urine. Using HOLCs to stabilize the anastomotic suture near renal pelvis should be avoided to prevent this complication. Instead, knotting is a better choice under such condition. The secondary calculi and dislodged HOLCs can be removed through PNL by an alligator plier after laser lithotripsy.

Abstract Background MTHFD1 gene may affect the embryonic development by elevated homocysteine levels, DNA synthesis and DNA methylation, but limited number of genetic variants of MTHFD1 gene was focused on the association with congenital heart disease (CHD). This study examined the role of MTHFD1 gene and maternal smoking on infant CHD risk, and investigated their interaction effects in Chinese populations. Methods A case-control study of 464 mothers of CHD infants and 504 mothers of health controls was performed. The exposures of interest were maternal tobacco exposure, single nucleotide polymorphisms (SNPs) of maternal MTHFD1 gene. The logistic regression model was used for accessing the strength of association. Results Mothers exposed to secondhand smoke during 3 months before pregnancy (adjusted odds ratio [aOR] = 1.56; 95% confidence interval [CI]: 1.13–2.15) and in the first trimester of pregnancy (aOR = 2.24; 95%CI: 1.57–3.20) were observed an increased risk of CHD. Our study also found that polymorphisms of maternal MTHFD1 gene at rs1950902 (AA vs. GG: aOR = 1.73, 95% CI: 1.01–2.97), rs2236222 (GG vs. AA: aOR = 2.38, 95% CI: 1.38–4.12), rs1256142 (GA vs.GG: aOR = 1.57, 95% CI: 1.01–2.45) and rs11849530 (GG vs. AA: aOR = 1.68, 95% CI: 1.02–2.77) were significantly associated with higher risk of CHD. However, we did not observe a significant association between maternal MTHFD1 rs2236225 and offspring CHD risk. Furthermore, we found the different degrees of interaction effects between polymorphisms of the MTHFD1 gene including rs1950902, rs2236222, rs1256142, rs11849530 and rs2236225, and maternal tobacco exposure. Conclusions Maternal polymorphisms of MTHFD1 gene, maternal tobacco exposure and their interactions are significantly associated with the risk of CHD in offspring in Han Chinese populations. However, more studies in different ethnic populations with a larger sample and prospective designs are required to confirm our findings. Trial registration Registration number: ChiCTR1800016635 .

Battery energy storage system is one of the most important and effective means to achieve carbon neutrality, its large-scale applications put forward higher requirements for the battery operating safety. Accurate and real-time battery state estimation is an important function of battery management systems, and it provides critical information for ensuring safe and reliable operation of batteries. However, it is not an easy task to accurately estimate the battery internal state due to the complex operating conditions and the complicated electrochemical reactions inside the battery. This paper provided a systematic review of the state-of-the-art techniques on the state of charge (SOC) and state of health (SOH) estimation of batteries. The advantages and main challenges existing in practical applications of different techniques were analyzed and compared. Then, the future development needs for battery SOC and SOH estimation techniques were prospected, which provides references for further research in battery state estimation

BackgroundWith the current global epidemic of obesity, especially among men, there is a need to understand its impact on adverse pregnancy outcomes. This study aimed to assess whether paternal pre-pregnancy body mass index (BMI) was associated with preterm birth and low birth weight in offspring.MethodsMultinomial logistic regression model was used to analyze associations between paternal BMI and preterm birth and low birth weight in different subgroups, the final model was adjusted for confounding factors of mothers and fathers. Further subgroup analysis was conducted to explore the stability of the risk associations.ResultsA total of 34,104 participants were included in this study, including 1,442 (4.2%) underweight, 13,930 (40.9%) overweight and 5,008 (14.7%) obese according to paternal BMI. The total incidence of preterm birth was 11.85% (4041/34104), and the incidence of low birth weight was 8.86% (3020/34104). In the total study population, compared with normal weight men, paternal pre-pregnancy overweight or obese was associated with a significantly increased risk of preterm birth [aOR; 95% CI respectively (1.34; 1.25–1.45 vs. 1.26; 1.14–1.40)] and low birth weight [aOR; 95% CI respectively (1.60; 1.46–1.74 vs. 1.40; 1.25–1.58)] in offspring. The results of subgroup analysis showed that the direction of the risk association was consistent, indicating good stability.ConclusionPaternal pre-pregnancy overweight and obesity were associated with an increased risk of preterm birth and low birth weight in their offspring.

BackgroundTo systematically evaluate the association of MTHFR genetic polymorphisms, maternal folic acid intake, and the time when folic acid intake was started with the risk of congenital heart disease (CHD) and investigated the role of their interaction on infant CHD risk in Chinese populations.MethodsA case–control study involving 592 CHD cases, 617 health controls, and their mothers was performed. The exposures of interest were single nucleotide polymorphisms (SNPs) of the MTHFR gene, maternal folic acid use, and the time when folic acid use was started. We applied the logistic regression model to explore the strength of association.ResultsOur findings showed that mothers lacking folic acid intake had a significantly higher risk of CHD in offspring (aOR = 2.00; 95%CI: 1.34–2.98). Mothers who started to use folic acid from the first trimester of the fetation (aOR = 1.65; 95% CI: 1.22–2.23) or from the second trimester of the fetation (aOR = 7.77; 95% CI: 2.52–23.96), compared with those starting to use folic acid from 3 months previous to the conception, were at a significantly higher risk of CHD in offspring. Genetic variants at rs2066470 (AA vs. GG: aOR = 5.09, 95%CI: 1.99–13.03), rs1801133 (AA vs. GG: aOR = 2.49, 95%CI: 1.58–3.93), and rs1801131 (TG vs. TT: aOR = 1.84, 95%CI: 1.36–2.50; GG vs. TT: aOR = 3.58, 95%CI: 1.68–7.63) were significantly associated with the risk of CHD based on the multivariate analysis. Additionally, statistically significant interactions between maternal folic acid intake and genetic variants of the MTHFR gene at rs1801133 and rs1801131 were observed.ConclusionAn association of maternal folic acid intake and the time when intake was started with the risk of CHD in offspring was found. What's more, maternal folic acid fortification may help counteract partial of the risks of CHD in offspring attributable to MTHFR genetic mutations.Registration numberhttp://www.chictr.org.cn/edit.aspx?pid=28300&htm=4, identifier: ChiCTR1800016635.

BackgroundWith the increase in maternal antidepressant prescribing before/during pregnancy, concerns about the safety of antidepressants have come into focus. The purpose of this study was to explore the association between maternal antidepressant use before pregnancy/in early pregnancy and the risk of congenital heart disease (CHD) in children, and to provide a scientific basis for clinical safety of antidepressant use.MethodsThe prospective cohort study ultimately included 34,104 singleton pregnancies. Modified Poisson regression model with robust error variances was used to evaluate RRs and 95% confidence intervals (CIs) for the risk of CHD in offspring exposed to maternal antidepressant in the 3 months before pregnancy and early pregnancy. In addition, sensitivity analysis was further performed to explore the robustness of the results.ResultsIn this study, the maternal antidepressant exposure rate was 2.83% in the 3 months before pregnancy, 2.42% in early pregnancy, and the incidence of CHD was 8.973 per 1,000 live births. We found that maternal antidepressant use in the 3 months before pregnancy and early pregnancy were all associated with an increased risk of CHD, ~2.54 times and 2.87 times, respectively, of non-use of antidepressants after adjusting for potential confounders. This association was also found in CHD specific phenotypic analysis. Of these, offspring whose mothers were exposed to antidepressants in the 3 months before pregnancy had the highest risk of transposition of the great arteries (aOR = 5.50, 95% CI: 1.91–15.88). The offspring of mothers exposed to antidepressants in early pregnancy had the highest risk of developing ventricular septal defect (aOR = 4.80, 95% CI: 2.50–9.24). Sensitivity analysis verified the stability of the results.ConclusionsMaternal antidepressant use in the 3 months before pregnancy and early pregnancy were all associated with an increased risk of CHD in their offspring. In order to reduce the risk of teratogenesis, we recommend that pregnant women prepare for pregnancy after their condition improves or receive the minimum effective dose of medication.

Abstract Background Although many studies showed that the risk of congenital heart disease (CHD) was closely related to genetic factors, the exact pathogenesis is still unknown. Our study aimed to comprehensively assess the association of single nucleotide polymorphisms (SNPs) of maternal MTHFR gene with risk of CHD and its three subtypes in offspring. Methods A case–control study involving 569 mothers of CHD cases and 652 health controls was conducted. Thirteen SNPs were detected and analyzed. Results Our study showed that genetic polymorphisms of maternal MTHFR gene at rs4846052 and rs1801131 were significantly associated with risk of CHD in the homozygote comparisons (TT vs. CC at rs4846052: OR = 7.62 [95%CI 2.95–19.65]; GG vs. TT at rs1801131: OR = 5.18 [95%CI 2.77–9.71]). And six haplotypes of G–C (involving rs4846048 and rs2274976), A–C (involving rs1801133 and rs4846052), G–T (involving rs1801133 and rs4846052), G–T–G (involving rs2066470, rs3737964 and rs535107), A–C–G (involving rs2066470, rs3737964 and rs535107) and G–C–G (involving rs2066470, rs3737964 and rs535107) were identified to be significantly associated with risk of CHD. Additionally, we observed that a two-locus model involving rs2066470 and rs1801131 as well as a three-locus model involving rs227497, rs1801133 and rs1801131 were significantly associated with risk of CHD in the gene–gene interaction analyses. For three subtypes including atrial septal defect, ventricular septal defect and patent ductus arteriosus, similar results were observed. Conclusions Our study indicated genetic polymorphisms of maternal MTHFR gene were significantly associated with risk of fetal CHD in the Chinese population. Additionally, there were significantly interactions among different SNPs on risk of CHD. However, how these SNPs affect the development of fetal heart remains unknown, and more studies in different ethnic populations and with a larger sample are required to confirm these findings.

BackgroundGiven that the time lag between cytomegalovirus (CMV) screening and diagnosed testing, a better knowledge of the association between pregnant women with CMV screening test positive and stillbirth in an epidemiological perspective was required to assist people being counseled reframe their pregnancy and birth plans based on the magnitude of the risk.MethodsThis study recruited 44048 eligible pregnant women from March 13, 2013 to December 31, 2019. Serological tests including CMV-specific IgM and IgG, and IgG avidity index were used to screen for maternal CMV infection and were measured by automated chemiluminescence immunoassay. The association was assessed using the inverse probability of group-weighted multivariate-adjusted log-binomial models.ResultsA total of 540 infants ended with a stillbirth (12.3 per 1000 pregnancies), and 2472 pregnancies with maternal CMV infection were screened out (56.1 per 1000 pregnancies) among all eligible pregnancies. In the comparison analysis, 326 infants ended with a stillbirth (86.6 per 1000 pregnancies) in the maternal CMV infection group compared with 214 infants (7.8 per 1000 pregnancies) in the group where mothers were not infected with CMV (RR 12.17; 95% CI 9.43–15.71). After excluding the pregnancies of stillbirth with birth defects, a strong association between the two groups was still observed (RR 9.38; 95% CI 6.92–12.70).ConclusionOur findings quantified the risk of a woman having a baby with stillbirth if she had a positive serologic CMV screening test in her first trimester, and supported the value of using CMV serologic tests as part of regular testing in pregnant women.Trial registrationRegistered in Chinese Clinical Trial Registry Center; registration number, ChiCTR1800016635; registration date, 06/14/2018 (Retrospectively registered); URL of trial registry record, https://www.chictr.org.cn/showproj.aspx?proj=28300.

ObjectiveTo estimate the association of selected maternal and fetal characteristics with the risk of perinatal mortality in South China.MethodsA prospective cohort study was conducted from March 2013 to December 2019. The exposures of interest were maternal sociodemographic characteristics, lifestyle and habits during early pregnancy, and complications of pregnancy. Their effects on the development of perinatal death were analyzed in our study.ResultsA total of 44,048 eligible pregnant women were included in the analysis. Of these, 596 fetuses were perinatal deaths (perinatal mortality was 13.5 per 1,000 births). After adjustment, maternal obesity, being employed, history of gestational hypertension, taking antidepressants during early pregnancy, history of gestational diabetes mellitus, gestational diabetes mellitus, infertility drug treatment and assisted reproductive techniques, history of neonatal death, preterm birth, and congenital malformations all significantly increased the risk of perinatal death. Ethnic minority, income > 5,000, multiparous women, and cesarean section associated with reduced risk of perinatal death.ConclusionSome factors of maternal sociodemographic characteristics, abnormal pregnancy history, lifestyle and habits during early pregnancy, and complications of pregnancy were associated with the risk of perinatal death.

BackgroundAlthough research indicates an association between hypertensive disorders of pregnancy (HDP) and congenital heart defects (CHDs) in offspring, consistency is still lacking. Therefore, we aimed to synthesize the updated published epidemiologic evidence to estimate the association of maternal HDP with the risk of total CHDs and its phenotypes in offspring.MethodsA systematic search of Web of Science Database, PubMed, and Embase were searched from inception through April 30, 2021 based on a preprepared protocol, and the reference lists were also manually searched. The combined risk estimates were calculated using either the fixed-effect models or random-effect models. Possible heterogeneity moderators were detected by subgroup, sensitivity analyses, and Galbraith plot.ResultsTwenty-four studies involving 477,839 CHDs cases among 40,394,699 participants were included in our meta-analysis. Mothers who had HDP exposure were significantly associated with an increased risk of total CHDs compared with non-exposure. When maternal HDP exposure was further subdivided into pre-eclampsia (OR = 1.79, 95% CI: 1.50–2.13), gestational hypertension (OR = 1.16, 95% CI: 1.02–1.31), and chronic hypertension (OR = 1.68, 95% CI: 1.49–1.89), a significantly increased risk of total CHDs were still presented. Furthermore, a statistically significant increased association was found between maternal HDP exposure and most CHD phenotypes. Besides, relevant heterogeneity moderators have been identified by subgroup and sensitivity analyses.ConclusionOur study suggested that maternal HDP exposure may be associated with an increase in the risk of CHDs in offspring. These findings highlight the need for greater surveillance of pregnant women with HDP exposure to allow early prevention that may be good for reducing the risk of CHDs in offspring.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [CRD42021268093].

ObjectivesThis study aimed at assessing the association between maternal methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) gene polymorphisms, maternal dietary habits, and their interactions with the risk of ventricular septal defects (VSD) in offspring.MethodsFrom November 2017 to March 2019, a case-control study comprising 360 mothers of VSD cases and 504 mothers of healthy infants was conducted in Han Chinese populations. The main exposures of interest were maternal dietary habits in early pregnancy and MTHFD1 gene polymorphisms. Logistic regression models were used to estimate the main effects and interaction effects.ResultsIt was observed that maternal excessive intake of pickled vegetables (aOR = 1.85, 95%CI: 1.45–2.37), smoked foods (aOR = 1.93, 95%CI: 1.48–2.51), barbecued foods (aOR = 1.74, 95%CI: 1.28–2.36), and fried foods (aOR = 1.68, 95%CI: 1.30–2.17) were associated with a higher risk of VSD in offspring, whereas maternal excessive intake of fresh meat (aOR = 0.61, 95%CI: 0.47–0.79), fish and shrimp (aOR = 0.29, 95%CI: 0.23–0.38), fresh eggs (aOR = 0.54, 95%CI: 0.42–0.70), fresh fruits or vegetables (aOR = 0.44, 95%CI: 0.33–0.60), soy foods (aOR = 0.65, 95%CI: 0.53–0.80), and milk products (aOR = 0.49, 95%CI: 0.40–0.59) could contribute significantly to a lower risk of VSD in offspring. Furthermore, the genetic polymorphisms of maternal MTHFD1 gene at rs1950902 (GA vs. GG: aOR = 0.67, 95%CI: 0.50–0.90) and rs2236222 (GG vs. AA: aOR = 2.75, 95%CI: 1.57–4.83) were significantly associated with the risk of VSD in offspring. In addition, there was a significant interaction effect between maternal dietary habits and MTHFD1 gene polymorphisms on the risk of VSD.ConclusionsMaternal dietary factors, MTHFD1 genetic polymorphisms, and their interactions were all associated with the risk of VSD in offspring. However, further research in diverse ethnic populations and with a larger sample size is warranted to corroborate our findings.Trial RegistrationRegistered in Chinese Clinical Trial Registry Center; registration number, ChiCTR1800016635; registration date, 06/14/2018 (Retrospectively registered); URL of trial registry record, https://www.chictr.org.cn/showproj.aspx?proj=28300.

Background. Congenital heart disease (CHD) is one of the most common birth defects among newborns, accounting for a large proportion of infant mortality worldwide. However, the mechanisms remain largely undefinable. This study aimed to investigate the association of CHD in offspring of mothers with diabetes mellitus (DM) and single nucleotide polymorphisms (SNPs) of NKX2.5. Methods and Results. A case-control study of 620 mothers of CHD patients and 620 mothers of healthy children admitted to Hunan Children’s Hospital from November 2017 to December 2019 was conducted. We collected the mothers’ information by questionnaire and detected children’s NKX2.5 variants with a MassARRAY system. The interaction coefficient (γ) was used to quantify the estimated gene-environment interactions. Univariate and multivariate analyses both showed that the infants had a higher risk of CHD if their mothers had a history of DM, including gestational DM (GDM) during this pregnancy (adjusted odds ratio [aOR=4.98]), GDM in previous pregnancies (aOR=4.30), and pregestational DM (PGDM) in the 3 months before this pregnancy (aOR=6.78). Polymorphisms of the NKX2.5 gene at rs11802669 (C/C vs. T/T: aOR=4.97; C/T vs. T/T: aOR=2.15) and rs2277923 (T/T vs. C/C, aOR=1.74; T/C vs. C/C, aOR=1.61) were significantly associated with the risk of CHD in offspring. In addition, significant interactions between maternal DM and NKX2.5 genetic variants at rs11802669 (aOR=8.12) and rs2277923 (aOR=17.72) affecting the development of CHD were found. Conclusions. These results suggest that maternal DM, NKX2.5 genetic variants, and their interactions are significantly associated with the risk of CHD in offspring.

Lithium-ion batteries have been widely used as energy storage systems and in electric vehicles due to their desirable balance of both energy and power densities as well as continual falling price. Accurate estimation of the state-of-charge (SOC) of a battery pack is important in managing the health and safety of battery packs. This paper proposes a compact radial basis function (RBF) neural model to estimate the state-of-charge (SOC) of lithium battery packs. Firstly, a suitable input set strongly correlated with the package SOC is identified from directly measured voltage, current, and temperature signals by a fast recursive algorithm (FRA). Secondly, a RBF neural model for battery pack SOC estimation is constructed using the FRA strategy to prune redundant hidden layer neurons. Then, the particle swarm optimization (PSO) algorithm is used to optimize the kernel parameters. Finally, a conventional RBF neural network model, an improved RBF neural model using the two stage method, and a least squares support vector machine (LSSVM) model are also used to estimate the battery SOC as a comparative study. Simulation results show that generalization error of SOC estimation using the novel RBF neural network model is less than half of that using other methods. Furthermore, the model training time is much less than the LSSVM method and the improved RBF neural model using the two-stage method.

The whole mitochondrial genome sequence of Lepturichthys fimbriata was amplified by primer walking sequence method, and then the whole genome genetic map of mitochondrion was obtained and mapped. The mitochondrial genome of L. fimbriata is a double-strand ring-like molecule with a total length of 16,567bp. It contains 2 rRNA genes (12SrRNA and 16SrRNA), 13 protein-coding genes (COI, COII, COIII, ATP6, ATP8, ND1, ND2, ND3, ND4, ND4L, ND5, ND6, Cytb), 22 tRNA coding genes, and one non-coding control region (D-loop control region). The overall nucleotide composition was A: 30.4%, T: 24.4%, C: 28.7%, and G: 16.5%, exhibiting an A + T bias of 54.8%. Phylogeny showed the phylogenetic relationships of different genera in the family Balitoridae and found the genus Lepturichthys is clustered with the genus Jinshaia, which suggested the intergeneric hybridization has likely occurred in both lineages.

BackgroundPatients with knee osteoarthritis (KOA) often present lower extremity motor dysfunction. However, traditional radiography is a static assessment and cannot achieve long-term dynamic functional monitoring. Plantar pressure signals have demonstrated potential applications in the diagnosis and rehabilitation monitoring of KOA. ObjectiveThrough wearable gait analysis technology, we aim to obtain abundant gait information based on machine learning techniques to develop a simple, rapid, effective, and patient-friendly functional assessment model for the KOA rehabilitation process to provide long-term remote monitoring, which is conducive to reducing the burden of social health care system. MethodsThis cross-sectional study enrolled patients diagnosed with KOA who were able to walk independently for 2 minutes. Participants were given clinically recommended functional tests, including the 40-m fast-paced walk test (40mFPWT) and timed up-and-go test (TUGT). We used a smart shoe system to gather gait pressure data from patients with KOA. The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. Furthermore, model stacking and average ensemble learning methods were adopted to further improve the generalization performance of the model. Mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE) were used as regression performance metrics to evaluate the results of different models. ResultsA total of 92 patients with KOA were included, exhibiting varying degrees of severity as evaluated by the Kellgren and Lawrence classification. A total of 380 gait features and 4 physical characteristics were extracted to form the feature database. Effective stepwise feature selection determined optimal feature subsets of 11 variables for the 40mFPWT and 10 variables for the TUGT. Among all models, the weighted average ensemble model using 4 tree-based models had the best generalization performance in the test set, with an MAE of 2.686 seconds, MAPE of 9.602%, and RMSE of 3.316 seconds for the prediction of the 40mFPWT and an MAE of 1.280 seconds, MAPE of 12.389%, and RMSE of 1.905 seconds for the prediction of the TUGT. ConclusionsThis wearable plantar pressure feature technique can objectively quantify indicators that reflect functional status and is promising as a new tool for long-term remote functional monitoring of patients with KOA. Future work is needed to further explore and investigate the relationship between gait characteristics and functional status with more functional tests and in larger sample cohorts.

This study investigated the effect of low-voltage electrostatic field on the flavor quality changes and generation pathways of refrigerated sturgeon caviar. Research has found that after storage for 3–6 weeks, the physicochemical properties of caviar in the LVEF treatment group are better than those in the control group. The results of two-dimensional gas chromatography-time-of-flight mass spectrometry showed that the contents of hexanal, nonanal, (E,Z)-2,6-nonadienal, (E)-2-octenal and 1-octene-3-one related to the characteristic flavor of caviar (sweet, fruity and green) increased significantly. The lipidomics results indicated that the effects of LVEF on caviar mainly involve glycerophospholipid metabolism, linoleic acid metabolism, and α-Linolenic acid metabolism. Methanophosphatidylcholine (15:0/18:1), phosphatidylcholine (18:0/20:5), and phosphatidylcholine (18,1e/22:6) were significantly correlated with odor formation. Therefore, low-voltage electrostatic field treatment preserved the quality and enhanced the flavor of sturgeon caviar. This study provided a new theoretical basis for the preservation of sturgeon caviar.

Multi-omics techniques were combined with microstructure, molecular sensory science and non-volatile matrices for the first time to investigate variations in organic macromolecules and flavor in caviar during preservation. After 4–6 weeks of storage, the peroxide value was 35.38 mg/g and the accumulation of thiobarbiturates was significant with caviar membranes exhibiting a decrease in elasticity and an increase in viscosity. Sixteen key volatile compounds were detected by GC–MS, while the volatile compounds that contributed to the differences in caviar flavor at different storage times were mainly tetradecane, (E)-2-hexenal, and heptanal. The pathways associated with flavor release during storage were mainly abundant in the linolenic acid metabolism, alanine metabolism, and glycerophospholipid metabolism pathways. The correlation of 11 differential proteins and 24 differential lipids with odorants was further explored, such as arginine, proline, alanine, PE (20:4/22:6), PE (16:1/18:2), and PE (20:5/18:2). Overall, Aspartate, glutamate, oleic acid, linoleic acid, and phospholipids enriched in C22:6 and C18:2 chains are potential metabolic markers. This study provides a basis from a multi-omics perspective for the investigation of the relationship between quality deterioration and precursor metabolism in caviar storage process.

To investigate the differences of volatile and non-volatile metabolites between oyster enzymatic hydrolysates and boiling concentrates, molecular sensory analysis and untargeted metabolomics were employed. “Grassy,” “fruity,” “oily/fatty,” “fishy,” and “metallic” were identified as sensory attributes used to evaluate different processed oyster homogenates. Sixty-nine and 42 volatiles were identified by gas chromatography–ion mobility spectrometry and gas chromatography–mass spectrometry, respectively. Pentanal, 1-penten-3-ol, hexanal, (E)-2-pentenal, heptanal, (E)-2-hexenal, 4-octanone, (E)-4-heptenal, 3-octanone, octanal, nonanal, 1-octen-3-ol, benzaldehyde, (E)-2-nonenal, and (E, Z)-2,6-nonadienal were detected as the key odorants (OAV > 1) after enzymatic hydrolysis. Hexanal, (E)-4-heptenal, and (E)-2-pentenal were significantly associated with off-odor, and 177 differential metabolites were classified. Aspartate, glutamine, alanine, and arginine were the key precursors affecting the flavor profile. Linking sensory descriptors to volatile and nonvolatile components of different processed oyster homogenates will provide information for the process and quality improvement of oyster products.

BackgroundDeafness is the most common sensory defect in humans worldwide. Approximately 50% of cases are attributed to genetic factors, and about 70% are non-syndromic hearing loss (NSHL).ObjectivesTo identify clinically relevant gene variants associated with NSHL in a Chinese family using trio-based whole-exome sequencing (WES).Materials and methodsWES was performed on the 18-month-old female proband, and her parents. Gene variants specific to the family were identified by bioinformatics analysis and evaluated for their relevance to NSHL. We verified the novel variant in this family by the next-generation sequencing.In order to elucidate the frameshift mutation of TMPRSS3 in a Chinese family, we used the Mass spectrometry to detect the gene from 1,010 healthy subjects.ResultsWe identified a novel homozygous deletion (c.51delA) in exon 2 of the type II transmembrane serine protease 3 gene TMPRSS3, which resulted in a frameshift mutation just before the protein transmembrane domain (p.Q17fs). The deletion was present in the proband and her father, but not in her mother and the healthy controls. We also found mutations with potential relevance to hearing loss in DCAF17, which encodes a protein of unknown function (c. T555A: p.H185Q), and ZNF276, which encodes zinc finger protein 276 (c.1350–2A > G).Conclusions and significanceWe shown a novel frameshift mutation in TMPRSS3 associated with autosomal recessive NSHL in a Han Chinese family.

Phase field description of fracture is a very promising approach for simulating crack initiation, propagation, merging and branching. This method greatly reduces the implementation complexity, compared with discrete descriptions of cracks. In this work, we provide an overview of phase field models for quasistatic and dynamic cases. Afterward, we present useful vectors and matrices for the implementation of this method in two and three dimensions. [ABSTRACT FROM AUTHOR]

Human-robot collaboration (HRC) is a key feature to distinguish the new generation of robots from conventional robots. Relevant HRC topics have been extensively investigated recently in academic institutes and companies to improve human and robot interactive performance. Generally, human motor control regulates human motion adaptively to the external environment with safety, compliance, stability, and efficiency. Inspired by this, we propose an augmented approach to make a robot understand human motion behaviors based on human kinematics and human postural impedance adaptation. Human kinematics is identified by geometry kinematics approach to map human arm configuration as well as stiffness index controlled by hand gesture to anthropomorphic arm. While human arm postural stiffness is estimated and calibrated within robot empirical stability region, human motion is captured by employing a geometry vector approach based on Kinect. A biomimetic controller in discrete-time is employed to make Baxter robot arm imitate human arm behaviors based on Baxter robot dynamics. An object moving task is implemented to validate the performance of proposed methods based on Baxter robot simulator. Results show that the proposed approach to HRC is intuitive, stable, efficient, and compliant, which may have various applications in human-robot collaboration scenarios.