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Topological data analysis (TDA) has proven to be a potent approach for extracting intricate topological structures from complex and high-dimensional data. In this paper, we propose a TDA-based processing pipeline for analyzing multi-channel scalp EEG data. The pipeline starts with extracting both frequency and temporal information from the signals via the Hilbert–Huang Transform. The sequences of instantaneous frequency and instantaneous amplitude across all electrode channels are treated as approximations of curves in the high-dimensional space. TDA features, which represent the local topological structure of the curves, are further extracted and used in the classification models. Three sets of scalp EEG data, including one collected in a lab and two Brain–computer Interface (BCI) competition data, were used to validate the proposed methods, and compare with other state-of-art TDA methods. The proposed TDA-based approach shows superior performance and outperform the winner of the BCI competition. Besides BCI, the proposed method can also be applied to spatial and temporal data in other domains such as computer vision, remote sensing, and medical imaging. [ABSTRACT FROM AUTHOR]

In a classic study in 1946, Tolman et al. found that rodents chose the optimal path to a hidden goal location when given the option to take a shortcut. Subsequent studies, though, found mixed results, including a previous study in humans showing non-optimal response strategies. Here, we tested human participants in a virtual sunburst maze identical to that employed by Tolman. Across three different experiments, we found that participants consistently employed non-optimal response strategies involving either following the encoded route or using the light as a beacon cue. Adding distal boundary cues (Experiment 2) or enhancing idiothetic cues (Experiment 3) led to the same overall results. Our findings suggest participants' search strategies are often suboptimal when given the opportunity to spontaneously take a short cut. [ABSTRACT FROM AUTHOR]

Directly converting biomass-derived 5-hydroxymethylfurfural (HMF) to 2,5-bis(alkoxymethyl)furans (BAMFs) via a one-pot process in alcohol systems is a very important approach for the synthesis of high-quality biofuels; however, this approach is highly challenging because it simultaneously involves the cascading Meerwein–Ponndorf–Verley (MPV) reduction and etherification reactions. Thus, designing an acid–base bifunctional catalyst is extremely desirable. Herein, we employed a glucose-based carbonaceous solid acid as a cheap organic ligand to prepare a series of new-type sulfonated zirconium–carbon coordination catalysts (Zr-GC-SO3H-X) via a simple solvothermal self-assembly method. By regulating the usage proportion of zirconium ions and organic ligand, Zr-GC-SO3H-1.0, possessing a proper Lewis/Brønsted acid ratio as well as strong Lewis acid–base (Zr4+–O2−) and Brønsted acid (–SO3H) sites, showed the optimum acid–base synergistic effects, so it displayed the highest catalytic performance. When the one-pot reductive etherification (OPRE) of HMF was performed in isopropanol, 2,5-bis(isopropoxymethyl)furan (BIPMF) yield could reach 95.8% in 6 h at 180 °C. Additionally, the analysis results of reaction processes demonstrated that the MPV reduction reaction of HMF was much easier than its etherification reaction in the presence of Zr-GC-SO3H-1.0, so initially forming 2,5-bis(hydroxymethyl)furan (BHMF) and then forming 2-hydroxymethyl-5-(isopropoxymethyl)furan (HIPMF) were the predominant reaction pathway for the OPRE of HMF to BIPMF. More significantly, Zr-GC-SO3H-1.0 also exhibited excellent universality and catalyzed the high-yield synthesis of various BAMFs in ethanol, n-propanol, n-butanol and sec-butanol. Conclusively, this work provided momentous references to construct high-efficiency catalysts for the OPRE of HMF. [ABSTRACT FROM AUTHOR]

Bisphenol A (BPA) is a widely used plastic material, but its potential endocrine disrupting effect has restricted its use. The BPA alternatives have raised concerns. This study aimed to compare inhibitory potencies of 11 BPA analogues on human and rat placental aromatase (CYP19A1). The inhibitory potency on human CYP19A1 ranged from bisphenol H (IC 50 , 0.93 μM) to tetramethyl BPA and tetrabromobisphenol S (ineffective at 100 μM) when compared to BPA (IC 50 , 73.48 μM). Most of them were mixed/competitive inhibitors and inhibited estradiol production in human BeWo cells. Molecular docking analysis showed all BPA analogues bind to steroid active site or in between steroid and heme of CYP19A1 and form a hydrogen bond with catalytic residue Met374. Pharmacophore analysis showed that there were 4 hydrophobic regions for BPA analogues, with bisphenol H occupying 4 regions. Bivariate correlation analysis showed that LogP (lipophilicity) and LogS (water solubility) of BPA analogues were correlated with their IC 50 values. Computerized drug metabolism and pharmacokinetics analysis showed that bisphenol H, tetrabromobisphenol A, and tetrachlorobisphenol A had low solubility, which might explain their weaker inhibition on estradiol production on BeWo cells. In conclusion, BPA analogues mostly can inhibit CYP19A1 and the lipophilicity determines their inhibitory strength. [Display omitted] • Some bisphenol A analogues potently inhibit placental CYP19A1. • Some bisphenol A analogues inhibit estradiol production by human BeWo cells. • Hydrophobicity determines the inhibitory strength of bisphenol A analogues on CYP19A1. • Most bisphenol A analogues bind to steroid-binding site and between steroid and heme of CYP19A1. [ABSTRACT FROM AUTHOR]

Judging how far away something is and how long it takes to get there is critical to memory and navigation. Yet, the neural codes for spatial and temporal information remain unclear, particularly the involvement of neural oscillations in maintaining such codes. To address these issues, we designed an immersive virtual reality environment containing teleporters that displace participants to a different location after entry. Upon exiting the teleporters, participants made judgments from two given options regarding either the distance they had traveled (spatial distance condition) or the duration they had spent inside the teleporters (temporal duration condition). We wirelessly recorded scalp EEG while participants navigated in the virtual environment by physically walking on an omnidirectional treadmill and traveling through teleporters. An exploratory analysis revealed significantly higher alpha and beta power for short-distance versus long-distance traversals, whereas the contrast also revealed significantly higher frontal midline delta–theta–alpha power and global beta power increases for short versus long temporal duration teleportation. Analyses of occipital alpha instantaneous frequencies revealed their sensitivity for both spatial distances and temporal durations, suggesting a novel and common mechanism for both spatial and temporal coding. We further examined the resolution of distance and temporal coding by classifying discretized distance bins and 250-msec time bins based on multivariate patterns of 2- to 30-Hz power spectra, finding evidence that oscillations code fine-scale time and distance information. Together, these findings support partially independent coding schemes for spatial and temporal information, suggesting that low-frequency oscillations play important roles in coding both space and time. [ABSTRACT FROM AUTHOR]

The use of alternative substances to replace bisphenol A (BPA) has been encouraged. The objective of this study was to evaluate the effects of BPA and 9 BPA alternatives on human and rat aromatase (CYP19A1) in human and rat placental microsomes. The results revealed that bisphenol A, AP, B, C, E, F, FL, S, and Z, and 4,4′-thiodiphenol (TDP) inhibited human CYP19A1 and bisphenol A, AP, B, C, FL, Z, and TDP inhibited rat CYP19A1. The IC 50 values of human CYP19A1 ranged from 3.3 to 172.63 μM and those of rat CYP19A1 ranged from 2.20 to over 100 μM. BPA alternatives were mixed/competitive inhibitors and inhibited estradiol production in BeWo placental cells. Molecular docking analysis showed that BPA alternatives bind to the domain between heme and steroid and form a hydrogen bond with catalytic residue Met374. Pharmacophore analysis showed that there were one hydrogen bond donor, one hydrophobic region, and one ring aromatic hydrophobic region. Bivariate correlation analysis showed that molecular weight, alkyl atom weight, and LogP of BPA alternatives were inversely correlated with their IC 50 values. In conclusion, BPA alternatives can inhibit human and rat CYP19A1 and the lipophilicity and the substituted alkyl size determines their inhibitory strength. [Display omitted] • Bisphenol A (BPA) alternatives inhibit human placental CYP19A1. • Some BPA alternatives suppress estradiol production by human BeWo cells. • Hydrophobicity determines the inhibitory strength of BPA alternatives on CYP19A1. • BPA alternatives bind to steroid-binding site and domain between steroid and heme of CYP19A1. [ABSTRACT FROM AUTHOR]

Discrete cosine transform (DCT) is an indispensable module in video codecs and is a major part in many video coding standards including the latest high efficiency video coding (HEVC). As the video resolution increases, both transform sizes and the number of transforms increase continuously which poses challenges to the reusability design especially in hardware implementation. This paper presents reconfigurable transform architecture to flexibly support the reusability of different transform sizes. The proposed architecture maximally reuses the hardware resources by rearranging the order of input data for different transform sizes while still exploiting the butterfly property. Furthermore, this architecture supports reconfigurable throughput according to different hardware resource requirements. By applying the proposed architecture to the field-programmable gate array (FPGA) design of HEVC core transform matrices, the synthesis results show much lower consumption of hardware resources comparing to existing methods in the literature. The implementation in Altera’s Stratix III FPGA can operate at 139 MHz and supports real-time processing of $3840\times 2160$ ultra-high definition video at a minimum of 45 f/s and up to 359 f/s for different DCT sizes. [ABSTRACT FROM AUTHOR]

• The role of apolipoprotein in the development of obesity. • Different apolipoproteins play different roles in lipid metabolism. • Apolipoprotein is a potential target for the treatment of obesity. Obesity is a state presented by excessive accumulation and abnormal distribution of body fat, with metabolic disorders being one of its distinguishing features. Obesity is associated with dyslipidemia and apolipoproteins are important structural components of plasma lipoproteins. Apolipoproteins influence the progression of obesity by a variety of mechanisms including lipid metabolism, energy expenditure and inflammatory response. In this review, we discuss the role of apolipoproteins in obesity, mechanisms of action as well as their potential as new therapeutic targets. [ABSTRACT FROM AUTHOR]

Antibiotics are widely consumed in the intensive mariculture industry. A better understanding of the effect of antibiotics on intergenerational antibiotic resistance in organisms is urgent since intergenerational transmission is crucial for the spread of antibiotic resistance genes (ARGs) in the environment. Herein, marine medaka (Oryzias melastigma) chronically exposed to low doses of sulfamethazine (SMZ) hormetically affected the progeny, characterized by increased richness and diversity of fecal microbiota and intestinal barrier-related gene up-regulation. Progeny immunity was modulated and caused by genetic factors due to the absence of significant SMZ accumulation in F1 embryos. In addition, some of the top genera in the progeny were positively correlated with immune diseases, while the expression of some immune-related genes, such as TNFα , IL1R2 , and TLR3 changed significantly. This further indicated that the host selection caused by changes in progeny immunity was probably the primary determinant of progeny intestinal microbial colonization. Metagenomic analysis revealed that Proteobacteria represented the primary carriers of ARGs, while parental SMZ exposure facilitated the distribution and enrichment of multiple ARGs involved in the antibiotic inactivation in the progeny by promoting the diversity of Gammaproteobacteria and Bacteroidetes, further illustrating that antibiotic selection pressure persisted even if the offspring were not exposed. Therefore, SMZ induced hormesis in the progeny at the expense of increasing antibiotic resistance. Collectively, these findings provide a comprehensive overview of the intergenerational effect of antibiotics and serve as a reminder that the ARG transmission induced by the intergenerational impact of antibiotics on organisms should not be ignored. [Display omitted] • Parental sulfamethazine exposure induced hormesis in the progeny of marine medaka. • Immune changes of progeny (host selection) determined gut microbial colonization. • Hormesis occurred in the progeny at the cost of increasing antibiotic resistance. • Gammaproteobacteria and Bacteroidetes were the dominant hosts of specific ARGs. [ABSTRACT FROM AUTHOR]

Determining bacterial identity at the strain level is critical for public health to enable proper medical treatments and reduce antibiotic resistance. Herein, we used liquid chromatography, ion mobility, and tandem MS (LC-IM-MS/MS) to distinguish Escherichia coli (E. coli) strains. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) showed the capability of this method to perform strain-level discrimination with prediction rates of 96.1% and 100% utilizing the negative and positive ion information, respectively. The tandem MS and LC separation proved effective in discriminating diagnostic lipid isomers in the negative mode, while IM separation was more effective in resolving lipid conformational biomarkers in the positive ion mode. Because of the clinical importance of early detection for rapid medical intervention, a faster technique, paper spray (PS)-IM-MS/MS, was used to discriminate the E. coli strains. The achieved prediction rates of the analysis of E. coli strains by PS-IM-MS/MS were 62.5% and 73.5% in the negative and positive ion modes, respectively. The strategy of numerical data fusion of negative and positive ion data increased the classification rates of PS-IM-MS/MS to 80.5%. Lipid isomers and conformers were detected, which served as strain-indicating biomarkers. The two complementary multidimensional techniques revealed biochemical differences between the E. coli strains confirming the results obtained from comparative genomic analysis. Moreover, the results suggest that PS-IM-MS/MS is a rapid, highly selective, and sensitive method for discriminating bacterial strains in environmental and food samples. [ABSTRACT FROM AUTHOR]

An important question regards the nature of our spatial memories for the paths that we have walked and, in particular, whether such distortions might violate the topological properties of the shape of the paths (i.e., creating an intersection when two paths did not intersect or vice versa). To investigate whether and how this might occur, we tested humans in situations in which they walked simple paths and idiothetic and visual cues either matched or mismatched, with the mismatching cues creating the greatest potential for topological distortions. Participants walked four-segment paths with 90° turns in immersive virtual reality and pointed to their start location when they arrived at the end of the path. In paths with a crossing, when the intersection was not presented, participants pointed to a novel start location suggesting a topological distortion involving non-crossed paths. In paths without a crossing, when a false intersection was presented, participants pointed to a novel start location suggesting a topological distortion involving crossed paths. In paths without crossings and without false intersections, participants showed reduced pointing errors that typically did not involve topological distortions. Distortions more generally, as indicated by pointing errors to the start location, were significantly reduced for walked paths involving primarily idiothetic cues with limited visual cues; conversely, distortions were significantly increased when idiothetic cues were diminished and navigation relied primarily on visual cues. Our findings suggest that our spatial memories for walked paths sometimes involve topological distortions, particularly when resolving the competition between idiothetic and visual cues. [ABSTRACT FROM AUTHOR]

Measuring changes in the stable isotope ratios of multiple elements (e.g. Δδ13C, Δδ37Cl, and Δδ2H) during the (bio)transformation of environmental contaminants has provided new insights into reaction mechanisms and tools to optimize remediation efforts. Dual-isotope analysis, wherein changes in one isotopic system are plotted against another (to derive an interpretational parameter expressed as Λ), is a key tool in multi-element isotopic assessment. To date, most dual-isotope analyses use ordinary linear regression (OLR) for the calculation, which can be subject to regression attenuation and thus an inherent artifact that depresses slope values, expressed as Λ. Here, a series of Monte Carlo simulations were constructed to represent common data conditions and variations within dual-isotope data to test the degree of bias when deriving Λ using OLR compared to an alternative regression technique, the York method. The degree of bias was quantified compared to the modeled or "true" Λ value. For all simulations, the York method provided the least bias in slope estimates (<1%) over all data conditions tested. In contrast, OLR produced unbiased estimates only under a limited set of conditions, which was validated through a mathematical model proof. Both the mathematical model and simulations show that bias of at least 5% in OLR occurs when the extent of enrichment in the x-variable (X M) is equal to or less than ≈15 times the 1σ precision in the isotope measurement (σ X), for both Cl/C and C/H plots. The results give practitioners tools to evaluate whether bias is present in data and to estimate the extent to which this negatively impacts the interpretations and predictions of remediation potential for new and previously published datasets. This study demonstrates that integration of such robust statistical tools is essential for dual-isotope interpretations widely used in contaminant hydrogeology but relevant to other disciplines including environmental chemistry and ecology. Image 1 • Mathematical proofs and Monte-Carlo simulations were used to quantify regression bias that significantly impacts dual-isotope analysis. • Minimal regression bias is observed when the extent of enrichment is ≥15 times the 1σ precision in the isotope measurement in the x-axis. • Findings are relevant to dual-isotope studies across disciplines. [ABSTRACT FROM AUTHOR]

The objective of this work is to tackle the challenges of monitoring and detecting subtle process changes in chemical mechanical planarization (CMP), an ultraprecision manufacturing process. Monitoring ultraprecision processes is usually of difficulty due to their innate complexity and low signal-to-noise ratio in sensor signals. Especially for subtle signal variations during small process changes, the conventional statistical process control charts could fail to detect such process anomalies from the sensor signals in the time domain. In this paper, frequency spectra representation of the microelectromechanical systems (MEMS) vibration sensor signals during subtle process changes is investigated, and the signal patterns uncovered by frequency spectra are utilized to formulate a machine learning–driven in situ process monitoring approach to detect process anomalies in CMP. The proposed approach overcomes the obstacles of differentiating subtle signal changes by transforming them into the frequency domain with Fourier transform and Hilbert-Huang transform and classifying the resulted frequency spectra with random forest. Based on frequency analysis, it can unveil the differences in the signals obscured in the time domain and suppress the high-frequency noise. Consequently, the presented machine learning–driven in situ process monitoring approach detects process anomalies by differentiating the deviated frequency spectra with machine learning. It is validated on our experimental CMP testbed for anomaly detection, and outperforms three benchmark statistical process control charts. For instance, it detects a slurry shutoff anomaly in CMP about ten times faster than the benchmark methods. [ABSTRACT FROM AUTHOR]

Laryngopharyngeal reflux disease (LPRD) is a condition characterized by the regurgitation of stomach and duodenal contents into the laryngopharynx, with variable and non-specific symptoms. Therefore, developing an accurate symptom scale for different regions is essential. Notably, the symptoms of "dryness and burning sensation in the laryngopharynx or mouth" are prevalent among the Chinese population but are often omitted from conventional symptom assessment scales, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) scales. To address this gap, our study incorporated the symptoms into the RSI and RSS-12 scales, developing the RSI-10/RSS-13 scales. Afterward, we assessed the role of the new scale's reliability (Cronbach's α and test–retest reliability), construct validity (confirmatory factor analysis and confirmatory factor analysis), and diagnostic efficiency. Our study encompassed 479 participants (average = 39.5 ± 13.4 years, 242 female) and 91 (average = 34.01 ± 13.50 years, 44 female) completed 24 h MII-pH monitoring. The Cronbach's α values of 0.80 and 0.82 for the RSI-10 and RSS-13 scales, respectively. RSI-10 and RSS-13 exhibited strong test–retest reliability (ICCs = 0.82–0.96) and diagnostic efficacy (AUC = 0.84–0.85). Furthermore, the factor analysis identified the RSS-13 and its three sub-scales (ear-nose-throat, digestive tract, respiratory tract) exhibited good to excellent structural validity (χ2/df = 1.95, P < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.05). The AUC optimal thresholds for the RSI-10 and RSS-13 in the Chinese population were 13 and 36, respectively. Besides, the inclusion of the new item significantly improved the diagnostic efficiency of the RSI scale (P = 0.04), suggesting that RSI-10 holds promise as a more effective screening tool for LPRD, and global validation is needed to demonstrate the impact of this new symptom on the diagnosis of LPRD. [ABSTRACT FROM AUTHOR]

Bisphenols, estrogenic endocrine-disrupting chemicals, disrupt at least one of three endocrine pathways (estrogen, androgen, and thyroid). 17β-Hydroxysteroid dehydrogenase 1 (17β-HSD1) is a steroidogenic enzyme that catalyzes the activation of estradiol from estrone in human placenta and rat ovary. However, whether bisphenols inhibit 17β-HSD1 and the mode of action remains unclear. This study we screened 17 bisphenols for inhibiting human 17β-HSD1 in placental microsomes and rat 17β-HSD1 in ovarian microsomes and determined 3D-quantitative structure-activity relationship (3D-QSAR) and mode of action. We observed some bisphenols with substituents were found to significantly inhibit both human and rat 17β-HSD1 with the most potent inhibition on human enzyme by bisphenol H (IC 50 = 0.90 μM) when compared to bisphenol A (IC 50 = 113.38 μM). Rat enzyme was less sensitive to the inhibition of bisphenols than human enzyme with bisphenol H (IC 50 = 32.94 μM) for rat enzyme. We observed an inverse correlation between IC 50 and hydrophobicity (expressed as Log P). Docking analysis showed that they bound steroid-binding site of 17β-HSD1. The 3D-QSAR models demonstrated that hydrophobic region, hydrophobic aromatic, ring aromatic, and hydrogen bond acceptor are key factors for the inhibition of steroid synthesis activity of 17β-HSD1. [Display omitted] • BPA analogues have been widely used but disrupt at least one of three endocrine pathways. • Bisphenols inhibit both human and rat 17β-HSD1. Rat enzyme was less sensitive than human enzyme. • Docking analysis showed that they bound steroid-binding site of 17β-HSD1. • 3D-QSAR models demonstrated HBA, HY, RA, HYA are key factors. • An inverse correlation between IC 50 and hydrophobicity (expressed as Log P). [ABSTRACT FROM AUTHOR]

Global climate change presents a significant threat to food security. Analyzing the effects of elevated ozone (O3) concentration on photosynthetic fluorescence characteristics and yield addresses the damage of climate change on crops, which would serve food security. With open-top chambers (OTCs) and Tiefeng-29 soybeans, we investigated the responses of chlorophyll concentration, fluorescence characteristics, net photosynthetic rate (Pn) and yield components to different O3 concentrations, which included CK (ambient concentration approximately 45 nL·L−1, T1 (80 ± 10) nL·L−1 and T2 (120 ± 10) nL·L−1 O3. The parent soybeans (S1) were planted in the current year, and O3 fumigation commenced 20 days after seedling emergence. Aeration was stopped at maturity, and the offspring soybeans (S2) were retained after harvest for further experiments. In the following year, S1 and S2 soybeans were planted, and O3 fumigation began 20 days after seedling emergence. The results show that leaf chlorophyll a (chla) and chlorophyll b (chlb) significantly decreased with longer O3 fumigation time both in parents and offspring, causing damage to the light-trapping ability while the offspring suffered an earlier decrease. The elevated O3 damaged the electron transfer process by significantly reducing the original and actual photochemical efficiencies of PSII both in parents and offspring. The electron transfer rate (ETR) of the parents and offspring decreased, while the difference between them was not significant after O3 treatment. The non-photochemical quenching coefficient (NPQ) showed an increasing trend along time but showed no significant difference between parents and offspring. An elevated concentration of O3 significantly reduced Pn, while the differences in Pn between the parents and the offspring were not significant. Elevated O3 resulted in reduced yields in both parent and offspring soybeans. Although it was found that the offspring soybeans exhibited higher yields than the parents, their reduction in yield was more significant. Therefore, elevated O3 concentration reduced soybean yield through damaging photosynthetic process and electron transfer capacity by impairing energy conversion and material accumulation capacity. The offspring had relatively higher light energy conversion efficiency than the parents, resulting in a higher yield than the parents under all treatments. [ABSTRACT FROM AUTHOR]

2,5-Bis(isopropoxymethyl)furan (BIPMF) is a typical biomass-derived furanic diether, which has been widely considered to be a high-quality biodiesel or diesel additive. At present, converting 5-hydroxymethylfurfural to BIPMF via a one-pot process is still challenging because it involves the Meerwein–Ponndorf–Verley (MPV) reduction and etherification reactions in isopropanol (iPrOH) at the same time. Hence, developing a bifunctional catalyst is highly necessary. In this work, sulfonic acid-functionalized zirconium-based coordination catalysts (Zr-BDC-Sx) were synthesized by a convenient solvothermal self-assembly approach, in which 1,4-benzenedicarboxylic acid (BDC) and 2-sulfo-1,4-benzenedicarboxylic acid monosodium (BDC-SO3Na) were used as dual ligands to regulate the acid–base properties of catalysts. Due to the superior cooperative actions of Lewis acid–base sites (Zr4+–O2−) and Brønsted acid sites (–SO3H), Zr-BDC-S60 displayed the highest catalytic activity, affording 100.0% HMF conversion and 96.9% BIPMF yield in 3 h at 120 °C. Furthermore, analysis of the reaction process proved that the MPV reduction of HMF to 2,5-bis(hydroxymethyl)furan (BHMF) followed by its etherification reaction was the preferential and principal reaction pathway for the formation of BIPMF in iPrOH over Zr-BDC-S60. Additionally, Zr-BDC-S60 was a robust catalyst and could be reused in at least three runs without an obvious loss in catalytic activity. To sum up, this work offered an easy-to-prepare and high-efficiency bifunctional catalyst for the one-pot reductive etherification of HMF to BIPMF, which provided excellent theoretical and technical references for the direct synthesis of BIPMF from biomass-derived carbohydrates. [ABSTRACT FROM AUTHOR]

There is a projection of 10 million deaths per year by 2050 due to antimicrobial resistance, highlighting the need for rapid detection and accurate identification of microorganisms. Herein, we used the paper spray technique coupled with ion mobility separation and tandem mass spectrometry (PS-IM-MS/MS) to rapidly discriminate and identify five Bacillus species in 2 min of analysis time after only 4 h of incubation time. Bacterial cells were harvested by filtering their liquid cultures and ionized directly by PS. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) allowed species-level discrimination with a prediction rate of 92.4% and 97.6% utilizing the negative and positive ion information of PS-MS/MS, respectively. However, upon including the biomarkers' corresponding drift times, i.e., PS-IM-MS/MS, prediction rates of ca. 99.7% and 100% were obtained utilizing the negative and positive ion information, respectively. We attributed the enhancement in the prediction rates to the capability of IM separations in resolving isomers. Surfactins and phospholipids were the major ion populations detected in our experiments. They were found to have various diagnostic isomers for various Bacillus species. Therefore, improved prediction rates could be obtained upon including high-resolution IM separations in the workflow. These proof-of-concept studies described here suggest that PS-IM-MS/MS workflow would enable rapid discrimination of closely related bacteria species and strains. [Display omitted] • Rapid bacteria detection and discrimination after only 4 h of incubation time and 2 min analysis time. • Ion mobility spectrometry enables the identification of biomarkers' isomers between bacteria species. • Five different Bacillus species were characterized with a success rate of 99%. • Collision cross-section measurement of surfactin and phospholipid isomers. [ABSTRACT FROM AUTHOR]

Zirconium-organic coordination catalysts (ZOCCs), possessing abundant zirconium–oxygen active species (Zr−Ox), have been widely used for the transformation of biomass-derived 5-hydroxymethylfurfural (HMF) to 2,5-bis(hydroxymethyl)furan (BHMF) via transfer hydrogenation (TH). However, most ZOCCs contain a high content of Zr and show low selectivity and turnover frequency (TOF) in primary alcohols, which greatly limit their practical application. In this work, we constructed a high-efficiency Zr-based single-atom catalyst (Zr/NC) with merely 0.58 wt% Zr by directly pyrolyzing Zr-doped ZIF-8. The experimental and theoretical results indicated that the atomically dispersed Zr–N4 coordination centers were confirmed to be the catalytic sites, and they displayed a fantastic catalytic activity. When isopropanol was used as a typical hydrogen donor, HMF could be completely converted with nearly 100% BHMF selectivity and 124.26 h−1 TOF in 150 min at 130 °C. More gratifyingly, when the hydrogen donor was switched to ethanol or n-butanol, the BHMF yield and selectivity were still more than 95% under appropriate reaction conditions. Such a remarkable performance should be principally attributed to the electron transfer from the pyridinic-N to Zr in Zr–N4 catalytic sites with high Lewis acid–base strengths, which could change the electron cloud densities of metal and ligand centers and then facilitate the formation of the target product. Additionally, mechanism studies revealed that the direct hydrogen transfer from the α-C of iPrOH to the carbonyl carbon of HMF on Zr–N4 catalytic sites was the rate-controlling step in the process of TH. Furthermore, Zr/NC could also exhibit excellent substrate applicability. To the best of our knowledge, this is the first work on the synthesis of a Zr-based single-atom catalyst with Zr–N4 catalytic sites to boost catalytic activity in the TH of biomass-derived carbonyl compounds. [ABSTRACT FROM AUTHOR]

Background: Depression is a prominent and highly prevalent nonmotor feature in patients with Parkinson's disease (PD). The neural and pathophysiologic mechanisms of PD with depression (DPD) remain unclear. The current diagnosis of DPD largely depends on clinical evaluation. Methods: We proposed a new family of multinomial tensor regressions that leveraged whole-brain structural magnetic resonance imaging (MRI) data to discriminate among 196 non-depressed PD (NDPD) patients, 84 DPD patients, 200 healthy controls (HC), and to assess the special brain microstructures in NDPD and DPD. The method of maximum likelihood estimation coupled with state-of-art gradient descent algorithms was used to predict the individual diagnosis of PD and the development of DPD in PD patients. Results: The results reveal that the proposed efficient approach not only achieved a high prediction accuracy (0.94) with a multi-class AUC (0.98) for distinguishing between NDPD, DPD, and HC on the testing set but also located the most discriminative regions for NDPD and DPD, including cortical regions, the cerebellum, the brainstem, the bilateral basal ganglia, and the thalamus and limbic regions. Conclusions: The proposed imaging technique based on tensor regression performs well without any prior feature information, facilitates a deeper understanding into the abnormalities in DPD and PD, and plays an essential role in the statistical analysis of high-dimensional complex MRI imaging data to support the radiological diagnosis of comorbidity of depression with PD. [ABSTRACT FROM AUTHOR]

Introduction: The current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD. Methods: In this study, we aimed to employ the radiomic approach to extract large‐scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting‐state functional connectivity (RSFC), amplitude of low‐frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel‐mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared. Results: The results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Conclusions: By identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy. [ABSTRACT FROM AUTHOR]

Camellia (Camellia oleifera Abel.) oil is a multifunctional woody oil known as the "Oriental olive oil". It is rich in oleic acid, sasanquasaponin and polyphenols and many other biological active substances with health-promoting properties, and has broad application prospects in the field of food, cosmetics and pharmaceuticals. As the increase of population health needs, the development and utilization of the nutritional and health care value of camellia oil has gradually become a hot spot for current research. This review comprehensively summarized the recent research progress on camellia oil, including the innovative extraction methods, novel analysis advances of bioactive components, and the recent pharmacological activities. Additionally, we also summarized the current research bottlenecks and possible solutions for developing and exploiting the health value of camellia oil. Various studies have reported that the content and composition of bioactive compounds in camellia oil are mainly influenced by extraction method and cultivation region, respectively. As an excellent resource of food and medicine, camellia oil has shown promising biological activities in both in vitro and animal studies. However, there are few clinical studies on the pharmacological activities of camellia oil. In the future, based on the large number of clinical studies, the mechanism of camellia oil for its health benefits can be further investigated in conjunction with lipidomics, proteomics, metabolomics and nutrigenomics research. • Camellia oil is rich in oleic acid and a variety of bioactive molecules. • Different cultivation region and extraction methods are key factors in the quality of camellia oil. • Camellia oil has a wide range of pharmacological applications. • Exploitation of camellia oil will generate significant economic, ecological and social benefits. [ABSTRACT FROM AUTHOR]

• Stable levels of SMZ accumulation and metabolic rates were observed in female fish. • Biotransformation of SMZ in males is susceptible to exposure concentrations. • Gut microbiome reactions to SMZ exhibit variations depending on sex. • Ruegeria acts as an indicator for the transmission of antibiotic resistance genes. The present study was undertaken to explore the effects of sulfamethazine (SMZ) dietary exposure on the enrichment of the intestine microbial structure, and antibiotic resistance gene (ARGs) transmission in marine medaka, with respect to antibiotic dose, duration, and sex. In male fish, a dietary exposure of 10 μg/L SMZ led to a heightened SMZ enrichment in the intestine, whereas metabolite (N-SMZ) levels were elevated at a higher exposure concentration (100 μg/L). Conversely, female fish exhibited stable levels of accumulation and metabolic rates across the exposure period. The composition of intestinal microorganisms revealed that exposure duration exerted a greater impact on the abundance and diversity of gut microbes, and microbial responses to SMZ varied across exposure time points. The expansion of Bacteroidetes and Ruegeria likely stimulated SMZ metabolism and contributed to the more balanced level of SMZ and N-SMZ observed in females. In males, short-term SMZ stress resulted in a disruption of intestinal homeostasis, while the rise in the abundance of the Fusobacteria and Propionigeniuma suggested a potential enhancement in intestinal anti-inflammatory capacity over time. Overall, female medaka exhibited greater adaptability to SMZ, and males appear to experience prolonged effects due to SMZ. A total of 11 ARGs and 5 mobile genetic elements (MGEs) were identified. Ruegeria is the main carrier of two types of MGEs (IS1247, ISSm2-Xanthob), and may serve as an indicator of ARG transmission. Therefore, it is rational to consider some fish breeding areas in natural waters as potential "reservoirs" of antibiotic resistance. This research will provide a valuable reference for the transmission of drug resistance along the food chain. [ABSTRACT FROM AUTHOR]

• 3D stereo machine vision and deep learning enable pine tree architecture analysis. • Tree stem diameter, branch angle, and branch diameter are automatically estimated. • The system can assist loblolly pine breeders in selection for superior tree form. Loblolly pine is one of the most planted forest tree species in the Southern United States for sawtimber production. The sawtimber yield potential of a pine tree is significantly impacted by its stem and branch architecture, which is of important focus in tree improvement programs. However, phenotyping these traits in the upper crown of pine trees is currently based on subjective visual assessments. This study investigated the feasibility of quantifying stem diameter, branch angle, and branch diameter of six-year-old loblolly pine trees in a progeny test using stereo 3D imaging, deep learning-based instance segmentation, and image and point cloud processing techniques. Instance segmentation of branches and stems was performed as well as principal component analysis (PCA) in 2D images, followed by 3D reconstruction of the segmented organs. The resulting 3D point clouds were further processed using random sample consensus (RANSAC) and statistical outlier removal to extract stem diameter, branch angle, and branch diameter. When compared to the manual ground-truth measurements, the three system-derived parameters achieved RMSEs of 0.055 m, 5.0˚, and 5.6 mm, respectively. In addition, Bland-Altman analyses showed that the stem diameter and branch angle estimations were found with limits of agreement of ± 0.098 m and ± 9.8˚, respectively, with nonsignificant biases. On the other hand, branch diameter estimation showed −12.1 mm and 9.3 mm for lower and upper limits of agreement with a bias. The proposed system demonstrates promising potential as a high-throughput low-cost precision phenotyping tool for the characterization of loblolly pine tree architecture under field conditions, facilitating the selection of superior genotypes with improved sawtimber properties. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a noninvasive method to record electrical activity of the brain. The EEG data is continuous flow of voltages, in this paper, we consider them as functional data, and propose a three-stage algorithm based on functional data analysis, with the advantage of interpretability. Specifically, the time and frequency information are extracted by wavelet transform in the first stage. Then, functional testing is utilized to select EEG channels and frequencies that show significant differences for different human behaviors. In the third stage, we propose to use penalized multiple functional logistic regression to interpretably classify human behaviors. With simulation and a scalp EEG data as validation set, we show that the proposed three-stage algorithm provides an interpretable classification of the scalp EEG signals. • Feature extraction and dimension reduction via functional data analysis. • Interpret-able three-stage algorithm for classifying scalp EEG. • Interpret-able functional data analysis of EEG data. [ABSTRACT FROM AUTHOR]