Employing Bidirectional Two-Sample Mendelian Randomization Analysis to Verify the Potential of Polyunsaturated Fatty Acid Levels in the Prevention of Pancreatic Cancer.

Polyunsaturated fatty acids (PUFAs), specifically Omega-3 (FAω3) and docosahexaenoic acid (DHA), have been studied for their potential role in modulating pancreatic cancer (PC) risk. Although observational studies suggest a beneficial effect in reducing this risk, their findings are often limited by confounding variables and issues of reverse causation. This study used a two-way two-sample Mendelian randomization (MR) method to test the hypothesized genetic causal relationship between PUFAs and PC risk. Data from an extensive genome-wide association study (GWAS) were analyzed, focusing on FAω3 and FAω6 levels, their ratios, and DHA as variables and PC incidence as outcomes. This relationship was comprehensively evaluated using related MR methods, such as inverse variance weighting (IVW), MR Egger, and weighted median (WM). This study finds a significant negative correlation between FAω3 and DHA levels and PC risk, while FAω6 levels show no significant correlation. Interestingly, the ratio of FAω6 to FAω3 was positively associated with increased risk of PC. Neither the MR Egger nor the MR-PRESSO tests detected significant pleiotropy, nor did the Cochrane's Q test show significant heterogeneity. Leave-one-out analyzes further confirmed the robustness of these results. Using MR analysis of two samples, this study provides genetic causal evidence that FAω3 and DHA levels reduce the risk of PC, whereas the ratio of FAω6 to FAω3 increases the risk of PC. These insights highlight the potential utility of supplementing FAω3 and DHA or altering PUFAs in developing PC prevention strategies.

Deep learning-enhanced snapshot hyperspectral confocal microscopy imaging system.

Laser-scanning confocal hyperspectral microscopy is a powerful technique to identify the different sample constituents and their spatial distribution in three-dimensional (3D). However, it suffers from low imaging speed because of the mechanical scanning methods. To overcome this challenge, we propose a snapshot hyperspectral confocal microscopy imaging system (SHCMS). It combined coded illumination microscopy based on a digital micromirror device (DMD) with a snapshot hyperspectral confocal neural network (SHCNet) to realize single-shot confocal hyperspectral imaging. With SHCMS, high-contrast 160-bands confocal hyperspectral images of potato tuber autofluorescence can be collected by only single-shot, which is almost 5 times improvement in the number of spectral channels than previously reported methods. Moreover, our approach can efficiently record hyperspectral volumetric imaging due to the optical sectioning capability. This fast high-resolution hyperspectral imaging method may pave the way for real-time highly multiplexed biological imaging.

Parameter Optimization for Interaction between C-Terminal Domains of HIV-1 Capsid Protein.

HIV-1 capsid proteins (CAs) assemble into a capsid that encloses the viral RNA. The binding between a pair of C-terminal domains (CTDs) constitutes a major interface in both the CA dimers and the large CA assemblies. Here, we attempt to use a general residue-level coarse-grained model to describe the interaction between two isolated CTDs in Monte Carlo simulations. With the standard parameters that depend only on the residue types, the model predicts a much weaker binding in comparison to the experiments. Detailed analysis reveals that some Lennard-Jones parameters are not compatible with the experimental CTD dimer structure, thus resulting in an unfavorable interaction energy. To improve the model for the CTD binding, we introduce ad hoc modifications to a small number of Lennard-Jones parameters for some specific pairs of residues at the binding interface. Through a series of extensive Monte Carlo simulations, we identify the optimal parameters for the CTD-CTD interactions. With the refined model parameters, both the binding affinity (with a dissociation constant of 13 ± 2 µM) and the binding mode are in good agreement with the experimental data. This study demonstrates that the general interaction model based on the Lennard-Jones potential, with some modest adjustment of the parameters for key residues, could correctly reproduce the reversible protein binding, thus potentially applicable for simulating the thermodynamics of the CA assemblies.

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model.

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

Updated roles of the gut microbiota in exploring shrimp etiology, polymicrobial pathogens, and disease incidence.

Litopenaeus vannamei is the most extensively cultured shrimp species globally, recognized for its scale, production, and economic value. However, its aquaculture is plagued by frequent disease outbreaks, resulting in rapid and massive mortality. etiological research often lags behind the emergence of new diseases, leaving the causal agents of some shrimp diseases unidentified and leading to nomenclature based on symptomatic presentations, especially in cases involving co- and polymicrobial pathogens. Comprehensive data on shrimp disease statuses remain limited. In this review, we summarize current knowledge on shrimp diseases and their effects on the gut microbiome. Furthermore, we also propose a workflow integrating primary colonizers, "driver" taxa in gut networks from healthy to diseased states, disease-discriminatory taxa, and virulence genes to identify potential polymicrobial pathogens. We examine both abiotic and biotic factors (e.g., external and internal sources and specific-disease effects) that influence shrimp gut microbiota, with an emphasis on the "holobiome" concept and common features of gut microbiota response to diverse diseases. After excluding the effects of confounding factors, we provide a diagnosis model for quantitatively predicting shrimp disease incidence using disease common-discriminatory taxa, irrespective of the causal agents. Due to the conservation of functional genes used in designing specific primers, we propose a practical strategy applying qPCR-assayed abundances of disease common-discriminatory functional genes. This review updates the roles of the gut microbiota in exploring shrimp etiology, polymicrobial pathogens, and disease incidence, offering a refined perspective for advancing shrimp aquaculture health management.

Advancing two-stage hydrogen production from corn stover via dark fermentation: Contributions of thermally modified maifanite to microbial proliferation and pH self-regulation.

This study introduces a two-stage hydrogen production enhancement mechanism using natural particle additives, with a focus on the effects of thermally modified maifanite (TMM) and pH self-regulation on dark fermentation (DF). Initial single-factor experiments identified preliminary parameters for the addition of TMM, which were further optimized using a Box-Behnken design. The established optimal conditions which include mass of 5.5 g, particle size of 120 mesh, and temperature of 324 °C, resulted in a 28.7 % increase in cumulative hydrogen yield (CHY). During the primary hydrogen production stage, TMM significantly boosted the growth and activity of Clostridium_sensu_stricto_1, enhancing hydrogen output. Additionally, a pH self-regulating phenomenon was observed, capable of initiating secondary hydrogen production and further augmenting CHY. These findings presented a novel and efficient approach for optimizing biohydrogen production, offering significant implications for future research and application in sustainable energy technologies.

Enhancing dark fermentative hydrogen production from wheat straw through synergistic effects of active electric fields and enzymatic hydrolysis pretreatment.

Hydrogen, a clean and sustainable energy source, faces challenges from energy-intensive pre-processing technologies. This study explores the synergistic enhancement of active electric fields on enzymolysis of wheat straw and hydrogen production through dark fermentation. The active electric field enzymolysis system improved the adsorption capacity of wheat straw to cellulase, increasing cellulase activity by 18.0 %, causing a 39.1 % increase in reducing sugar content. In the active fermentation system, Clostridium_sensu_stricto_1 activity was enhanced in the first stage, increasing hydrogenase activity by 23.0 %, prolonging the first hydrogen production peak. Elevated reducing sugars were observed in the second stage, with Prevotella_9 and Bacteroides becoming the dominant hydrogen-producing bacteria in the third stage, leading to a second hydrogen production peak. Overall, cumulative hydrogen production was enhanced by 50.9 % compared to the control. The synergistic pretreatment with an active electric field and cellulase provides a novel approach for efficiently utilizing wheat straw.

Natural and anthropogenic dissolved organic matter in landfill leachate: Composition, transformation, and their coexistence characteristics.

A large number of natural and anthropogenic wastes were landfilled, and dissolved organic matter (DOM) were formed during landfill. However, the composition, transformation, and coexistence characteristics of natural and anthropogenic DOM in leachate remain unclear. Fourier transform ion cyclotron resonance mass spectrometry, size exclusion chromatography, gas chromatography coupled with mass spectrometry, and three-dimensional excitation-emission matrix spectrum were employed to clarify comprehensively the abovementioned question. The results showed that natural DOM in young leachate constituted mainly straight-chain organic acids, protein substances, and building blocks of humic substances (BB). Straight-chain organic acids vanished in old leachates, and the concentration of protein substances and BB decreased from 44% to 26% and from 47% to 12%, respectively, while CHON and CHONS were degraded to CHO and CHOS during the process. As to anthropogenic DOM, its types and relative content in leachate increased during landfill, and aromatic acids, terpenes, halogenated organics, indoles, and phenols became the main organic components in old leachate. Compared to natural DOM, anthropogenic DOM was degraded slowly and accumulated in leachate, and some of the natural DOM facilitated the dechlorination of dichlorinated organic compounds. This study demonstrates that landfill led to an increase in humic substances and halogenated organic compounds in old leachate, which was intensified with concentrated leachate recirculation.

AudioGest: Gesture-based Interaction for Virtual Reality using Audio Devices.

Current virtual reality (VR) system takes gesture interaction based on camera, handle and touch screen as one of the mainstream interaction methods, which can provide accurate gesture input for it. However, limited by application forms and the volume of devices, these methods cannot extend the interaction area to such surfaces as walls and tables. To address the above challenge, we propose AudioGest, a portable, plug-and-play system that detects the audio signal generated by finger tapping and sliding on the surface through a set of microphone devices without extensive calibration. First, an audio synthesis-recognition pipeline based on micro-contact dynamics simulation is constructed to generate modal audio synthesis from different materials and physical properties. Then the accuracy and effectiveness of the synthetic audio are verified by mixing the synthetic audio with real audio proportionally as the training sets. Finally, a series of desktop office applications are developed to demonstrate the application potential of AudioGest's scalability and versatility in VR scenarios.

AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging.

Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models, and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A transfer learning framework is further devised to allow our AutoUnmix to adapt to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve the highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. For experiments where spectral profiles and morphology are akin to simulated data, our method realizes the quantitative performance demonstrated above. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool for studying the interaction process of different organelles labeled by multiple fluorophores.

Thermally modified tourmaline enhances hydrogen production by influencing hydrolysis acidification in two stages during dark fermentation of corn stover.

This study investigated the influence of thermally modified tourmaline (Tur) on hydrogen production during the dark fermentation of corn stover. Single-factor experimental results revealed influencing factors of particle size, mass, and temperature. Optimization of the experimental process was achieved using the Box-Behnken design, reaching optimum at conditions of 407 °C, 910-mesh, and 6.2 g. The principle analysis experiment showed that the Tur-enhanced group (Tur_En) amplified cumulative hydrogen production by elevating hydrogen production during the sugar-production stage. The Tur_En group's cumulative hydrogen production was measured at 396.2 ± 40.3 (mL/g VS), marking a 34.2% increase compared to the control group. Analysis of microbial diversity indicated that Firmicutes and Bacteroidota emerged as dominant colonies in both stages. Tur facilitated hydrogen production by stimulating the activity of Firmicutes. This study suggests a highly effective Tur-enhanced technology for hydrogen production from corn stover and elucidates the principles underpinning this method from two stages.

Detection of Alternaria alternata infection in winter jujubes based on optical properties and their correlation with internal quality parameters during storage.

In this work, a single integrating sphere system was applied to characterize the optical absorption (µa) and reduced scattering (µs') properties (550 - 1050 nm) in winter jujube flesh infected by Alternaria alternata during storage at 4 and 20 °C, respectively. Meanwhile, physical (L*, a*, weight loss) and biochemical characteristics (soluble solids content, titratable acids, chlorophyll, total phenolic, and ascorbic acid) of winter jujubes were measured. Among them, chlorophyll, weight loss and ascorbic acid were highly correlated with µa at 680 nm, 690 nm, while chlorophyll and a* had the best correlations with µs' at 700 - 920 nm. These optimal optical properties were proved efficiently contributed to the disease detection of winter jujubes after 12 days at 4 °C and 3 days at 20 °C during storage, with satisfactory discrimination accuracies (acc > 93.75 %). Consequently, optical properties in Vis-NIR region were available to detect the postharvest disease in winter jujubes.

Impact of mechanical ventilation control strategies based on non-steady-state and steady-state Wells-Riley models on airborne transmission and building energy consumption.

Ventilation is an effective solution for improving indoor air quality and reducing airborne transmission. Buildings need sufficient ventilation to maintain a low infection risk but also need to avoid an excessive ventilation rate, which may lead to high energy consumption. The Wells-Riley (WR) model is widely used to predict infection risk and control the ventilation rate. However, few studies compared the non-steady-state (NSS) and steady-state (SS) WR models that are used for ventilation control. To fill in this research gap, this study investigates the effects of the mechanical ventilation control strategies based on NSS/SS WR models on the required ventilation rates to prevent airborne transmission and related energy consumption. The modified NSS/SS WR models were proposed by considering many parameters that were ignored before, such as the initial quantum concentration. Based on the NSS/SS WR models, two new ventilation control strategies were proposed. A real building in Canada is used as the case study. The results indicate that under a high initial quantum concentration (e.g., 0.3 q/m3) and no protective measures, SS WR control underestimates the required ventilation rate. The ventilation energy consumption of NSS control is up to 2.5 times as high as that of the SS control.

Tourmaline enhanced methane yield via regulating microbial metabolic balance during anaerobic co-digestion of corn stover and cow manure.

This work performed a pilot-scale study on the effects of the substrate ratio, the concentration of tourmaline (Tur), and its high-temperature thermally modified (HTM) material on the anaerobic co-digestion of corn stover (CS) and cow manure (CM). The experimental results showed that the CH4 yield was higher at a corn stover -to- cow manure feeding ratio of 2:1. The cumulative CH4 yield increased by 22.76% and 8.31% at a concentration of tourmaline of 2.0 g/L and a tourmaline treatment temperature of 400 °C respectively. Microbial diversity analysis revealed that adding low doses of tourmaline regulated the distribution of microorganisms and that Methanobacteria became the dominant methanogenic archaea in the fermentation broth. This work clarified the effect of the concentration of tourmaline on gas production by anaerobic co-digestion from the perspective of the microbial metabolic balance and suggested the possibility of its application on a larger scale.

An unprecedented fully reduced {MoV 60} polyoxometalate: from an all-inorganic molecular light-absorber model to improved photoelectronic performance.

Fully reduced polyoxometalates are predicted to give rise to a broad and strong absorption spectrum, suitable energy levels, and unparalleled electronic and optical properties. However, they are not available to date. Here, an unprecedented fully reduced polyoxomolybdate cluster, namely Na8[MoV 60O140(OH)28]·19H2O {MoV 60}, was successfully designed and obtained under hydrothermal conditions, which is rare and is the largest fully reduced polyoxometalate reported so far. The MoV 60 molecule describes one Keggin {ε-Mo12} encapsulated in an unprecedented {Mo24} cage, giving rise to a double truncated tetrahedron quasi-nesting architecture, which is further face-capped by another four {Mo6} tripods. Its crystalline stability in air, solvent tolerance, and photosensitivity were all shown. As a cheap and robust molecular light-absorber model possessing wide light absorption, MoV 60 was applied to build a co-sensitized solar cell photoelectronic device along with N719 dyes and the optimal power conversion efficiency was 28% higher than that of single-dye sensitization. These results show that MoV 60 polyoxometalate could serve as an ideal model for the design and synthesis of all-inorganic molecular light-absorbers for other light-driven processes in the future.

Magnons in ferromagnetic metallic manganites.

Ferromagnetic (FM) manganites, a group of likely half-metallic oxides, are of special interest not only because they are a testing ground for the classical double-exchange interaction mechanism for the 'colossal' magnetoresistance, but also because they exhibit an extraordinary arena of emergent phenomena. These emergent phenomena are related to the complexity associated with strong interplay between charge, spin, orbital, and lattice. In this review, we focus on the use of inelastic neutron scattering to study the spin dynamics, mainly the magnon excitations in this class of FM metallic materials. In particular, we discuss the unusual magnon softening and damping near the Brillouin zone boundary in relatively narrow-band compounds with strong Jahn-Teller lattice distortion and charge-orbital correlations. The anomalous behaviours of magnons in these compounds indicate the likelihood of cooperative excitations involving spin and lattice as well as orbital degrees of freedom.

ATF3 promotes migration and M1/M2 polarization of macrophages by activating tenascin­C via Wnt/ß­catenin pathway.

There are different polarization states of macrophages, including the classically activated M1 phenotype and the alternatively activated M2 phenotype. These have different functions in the inflammation process. Activating transcription factor 3 (ATF3) is a key transcriptional regulator that inhibits the inflammatory response. However, the effects of ATF3 on migration and anti­inflammatory control mechanisms of macrophages have not been thoroughly investigated. The present study investigated the effect of ATF3 on macrophage migration and M1/M2 polarization. Results revealed that overexpression of ATF3 promoted macrophage migration and the expression of the M2 phenotype markers [cluster of differentiation (CD) 163, mannose receptor C type 1, arginase 1 and peroxisome proliferator­activated receptor γ] and inhibited expression of the M1 phenotype markers (monocyte chemoattractant protein­1, inducible nitric oxide synthase, CD16 and tumor necrosis factor­α), whereas knockdown of ATF3 resulted in a contrary effect. In addition, the wingless­type MMTV integration site family member (Wnt)/ß­catenin signaling pathway was activated and the expression level of tenascin (TNC) was significantly upregulated by overexpression of ATF3. Additionally, inhibition of Wnt/ß­catenin signaling significantly attenuated the upregulatory effect of ATF3 on TNC. Finally, the effect of ATF3 on macrophage migration and markers of the M1 or M2 state was investigated using TNC­specific siRNA. In conclusion, the results of the present study suggested that ATF3 promotes macrophage migration and reverses M1­polarized macrophages to the M2 phenotype by upregulation of TNC via the Wnt/ß­catenin signaling pathway.

An image guided small animal stereotactic radiotherapy system.

Small animal radiotherapy studies should be performed preferably on irradiators capable of focal tumor irradiation and healthy tissue sparing. In this study, an image guided small animal arc radiation treatment system (iSMAART) was developed which can achieve highly precise radiation targeting through the utilization of onboard cone beam computed tomography (CBCT) guidance. The iSMAART employs a unique imaging and radiation geometry where animals are positioned upright. It consists of a stationary x-ray tube, a stationary flat panel detector, and a rotatable and translational animal stage. System performance was evaluated in regards to imaging, image guidance, animal positioning, and radiation targeting using phantoms and tumor bearing animals. The onboard CBCT achieved good signal, contrast, and sub-millimeter spatial resolution. The iodine contrast CBCT accurately delineated orthotopic prostate tumors. Animal positioning was evaluated with ~0.3 mm vertical displacement along superior-inferior direction. The overall targeting precision was within 0.4 mm. Stereotactic radiation beams conformal to tumor targets can be precisely delivered from multiple angles surrounding the animal. The iSMAART allows radiobiology labs to utilize an image guided precision radiation technique that can focally irradiate tumors while sparing healthy tissues at an affordable cost.

[Degradation of styrene by coupling ultraviolet and biofiltration].

Purification of styrene by ultraviolet (UV)-biofiltration was studied in this paper. The light source and the biofilm carrier were ozone producing lamp at 185 nm and the peat, palm fiber, porous acticarbon, respectively. Styrene inlet concentration was controlled between 320-583 mg x m(-3), and the removal efficiency remained above 95% after stabilization. The UV converted styrene into more soluble and biodegradable intermediates, such as alcohol, aldehyde and acid, thus the performance of biofilter can be improved. In the stable operation stage, the variation of inlet concentration did not affect the removal efficiency when the total residence time (TRT) was long, however, the inlet concentration obviously affected the removal efficiency when the TRT decreased. The removal load of coupling system increased linearly with increasing inlet load, and the removal efficiency was higher than 95% under a TRT of 102 s. When TRT was 68 s and the inlet load was low, the variation of removal load complied with the law described above, but it gradually deviated from the straight line and tended to stabilized at a certain value when the inlet load became higher than 30 g x (m3 x h)(-). If considering the fluctuation of styrene concentration only, the contribution rate of ultraviolet photolysis to styrene removal was greater than that of the biofilter, and the removal effect could be restored on the fourth day, after closing the system for ten days and restarting.

Effects of cobalt precursor on pyrolyzed carbon-supported cobalt-polypyrrole as electrocatalyst toward oxygen reduction reaction.

A series of non-precious metal electrocatalysts, namely pyrolyzed carbon-supported cobalt-polypyrrole, Co-PPy-TsOH/C, are synthesized with various cobalt precursors, including cobalt acetate, cobalt nitrate, cobalt oxalate, and cobalt chloride. The catalytic performance towards oxygen reduction reaction (ORR) is comparatively investigated with electrochemical techniques of cyclic voltammogram, rotating disk electrode and rotating ring-disk electrode. The results are analyzed and discussed employing physiochemical techniques of X-ray diffraction, transmission electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, inductively coupled plasma, elemental analysis, and extended X-ray absorption fine structure. It shows that the cobalt precursor plays an essential role on the synthesis process as well as microstructure and performance of the Co-PPy-TsOH/C catalysts towards ORR. Among the studied Co-PPy-TsOH/C catalysts, that prepared with cobalt acetate exhibits the best ORR performance. The crystallite/particle size of cobalt and its distribution as well as the graphitization degree of carbon in the catalyst greatly affects the catalytic performance of Co-PPy-TsOH/C towards ORR. Metallic cobalt is the main component in the active site in Co-PPy-TsOH/C for catalyzing ORR, but some other elements such as nitrogen are probably involved, too.