Search

Abstract Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1 V (0.5 mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200 mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits.

Abstract Colorectal cancer (CRC) patients with liver metastases usually obtain less benefit from immunotherapy, and the underlying mechanisms remain understudied. Here, we identify that fibrinogen-like protein 1 (FGL1), secreted from cancer cells and hepatocytes, facilitates the progression of CRC in an intraportal injection model by reducing the infiltration of T cells. Mechanistically, tumor-associated macrophages (TAMs) activate NF-ĸB by secreting TNFα/IL-1β in the liver microenvironment and transcriptionally upregulate OTU deubiquitinase 1 (OTUD1) expression, which enhances FGL1 stability via deubiquitination. Disrupting the TAM-OTUD1-FGL1 axis inhibits metastatic tumor progression and synergizes with immune checkpoint blockade (ICB) therapy. Clinically, high plasma FGL1 levels predict poor outcomes and reduced ICB therapy benefits. Benzethonium chloride, an FDA-approved antiseptics, curbs FGL1 secretion, thereby inhibiting liver metastatic tumor growth. Overall, this study uncovers the critical roles and posttranslational regulatory mechanism of FGL1 in promoting metastatic tumor progression, highlighting the TAM-OTUD1-FGL1 axis as a potential target for cancer immunotherapy.

Background Suicidal attempts in patients with major depressive disorder (MDD) have become an important challenge in global mental health affairs. To correctly distinguish MDD patients with and without suicidal attempts, a multimodal prediction model was developed in this study using multimodality data, including demographic, depressive symptoms, and brain structural imaging data. This model will be very helpful in the early intervention of MDD patients with suicidal attempts. Methods Two feature selection methods, support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF) algorithms, were merged for feature selection in 208 MDD patients. SVM was then used as a classification model to distinguish MDD patients with suicidal attempts or not. Results The multimodal predictive model was found to correctly distinguish MDD patients with and without suicidal attempts using integrated features derived from SVM-RFE and RF, with a balanced accuracy of 77.78%, sensitivity of 83.33%, specificity of 70.37%, positive predictive value of 78.95%, and negative predictive value of 76.00%. The strategy of merging the features from two selection methods outperformed traditional methods in the prediction of suicidal attempts in MDD patients, with hippocampal volume, cerebellar vermis volume, and supracalcarine volume being the top three features in the prediction model. Conclusions This study not only developed a new multimodal prediction model but also found three important brain structural phenotypes for the prediction of suicidal attempters in MDD patients. This prediction model is a powerful tool for early intervention in MDD patients, which offers neuroimaging biomarker targets for treatment in MDD patients with suicidal attempts.

Abstract Metabolic enzymes have an indispensable role in metabolic reprogramming, and their aberrant expression or activity has been associated with chemosensitivity. Hence, targeting metabolic enzymes remains an attractive approach for treating tumors. However, the influence and regulation of cysteine desulfurase (NFS1), a rate-limiting enzyme in iron–sulfur (Fe–S) cluster biogenesis, in colorectal cancer (CRC) remain elusive. Here, using an in vivo metabolic enzyme gene-based clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 library screen, we revealed that loss of NFS1 significantly enhanced the sensitivity of CRC cells to oxaliplatin. In vitro and in vivo results showed that NFS1 deficiency synergizing with oxaliplatin triggered PANoptosis (apoptosis, necroptosis, pyroptosis, and ferroptosis) by increasing the intracellular levels of reactive oxygen species (ROS). Furthermore, oxaliplatin-based oxidative stress enhanced the phosphorylation level of serine residues of NFS1, which prevented PANoptosis in an S293 phosphorylation-dependent manner during oxaliplatin treatment. In addition, high expression of NFS1, transcriptionally regulated by MYC, was found in tumor tissues and was associated with poor survival and hyposensitivity to chemotherapy in patients with CRC. Overall, the findings of this study provided insights into the underlying mechanisms of NFS1 in oxaliplatin sensitivity and identified NFS1 inhibition as a promising strategy for improving the outcome of platinum-based chemotherapy in the treatment of CRC.

Conventional hydraulic fracturing techniques typically consume large amounts of water when producing shale gas. Fracking fluids may cause environmental pollution. In contrast, supercritical carbon dioxide (scCO2) (above 31.8°C, 7.29 MPa) can displace CH4 in shale reservoirs. Achieve CO2 sequestration while increasing the shale gas production. We studied the mechanical properties and fracture characteristics of a shale under the action of scCO2, nitrogen, helium, and water by comparing the triaxial compression tests of shale samples with seven coring angles. The results show that: (1) scCO2 effectively reduced compressive strength of the shale and weakened the anisotropy of shale; (2) scCO2 caused the content of dolomite, calcite, and illite to decrease by 4.7%∼13.5%, respectively; (3) scCO2 produced micropores and microfractures 10 times larger than the original size in the microstructure. These microstructures can help improve the seepage and gathering of shale gas, leading to enhanced shale gas recovery and CO2 storage.

The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-energy-consumption computing. Existing computing instruments are pre-dominantly electronic processors, which use electrons as information carriers and possess von Neumann architecture featured by physical separation of storage and processing. The scaling of computing speed is limited not only by data transfer between memory and processing units, but also by RC delay associated with integrated circuits. Moreover, excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption scaling. Using photons as information carriers is a promising alternative. Owing to the weak third-order optical nonlinearity of conventional materials, building integrated photonic computing chips under traditional von Neumann architecture has been a challenge. Here, we report a new all-optical computing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural networks. The device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed “weight modulators” to enable complete phase and amplitude control in each waveguide branch. The generic device concept can be used for equation solving, multifunctional logic operations as well as many other mathematical operations. Multiple computing functions including transcendental equation solvers, multifarious logic gate operators, and half-adders were experimentally demonstrated to validate the all-optical computing performances. The time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per bit. Our approach can be further expanded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical computing.

The problem of electrochemical corrosion of buried pipelines in near-neutral electrolytes leads to defects in or even fracture of oil and gas pipelines and the leakage of natural gas. Based on the principle of material diffusion and migration, the research object established an electrochemical corrosion model under the metallographic structure of pipes with ferritic–pearlitic pipeline steel. The results show that the most severe corrosion occurs at the center of the corrosion on the surface of the pipeline steel in a near-neutral corrosive environment. In addition, due to corrosion product accumulation, the material corrosion rate increased by about 38%. The electrolyte potential near the corrosion electrode is smaller, the ion concentration near the electrode is the highest, and the mass transfer phenomenon around the corrosion electrode is obvious. When the material undergoes metallographic corrosion, the corrosion is more severe. This research method can be used to predict the electrochemical corrosion occurring in the metal structure of buried pipelines and has some guidance for the assessment of the integrity of the external surface of buried pipes.

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Objective The QingYu pig is well known for its excellent meat quality attributes in Sichuan province, China. In order to improve its production efficiency, the determination of genetic factors contributing to quantifiable economic traits of livestock is important. Moreover, the cross-breeding of QingYu pigs with western breeds possessing strong growth attributes is an efficient way to improve the performance of this breed. Methods Here, the genetic parameters of several important reproductive traits of QingYu pigs were estimated, include total number born (TNB), number born alive, litter birth weight, individual birth weight, number of piglets weaned, litter weaning weight, and individual weaning weight. The data was analyzed using the ASReml 3.0 software (NSW Inc., Sydney, Australia). Furthermore, the effects of crossing Berkshire with QingYu (BQ) pigs on carcass and meat quality traits, as well as the effects of slaughter weight on carcass and meat quality of BQ were characterized. Results QingYu pigs exhibited superior reproductive traits. The TNB available to QingYu pigs was more than 8 per parity. The observed repeatability of the reproductive traits of the QingYu pigs was between 0.10 and 0.23. The significantly correlated genetic and phenotypic of reproduction traits were consistent. Interestingly, the BQ pigs exhibited improved carcass quality, with a significant increase in loin muscle area, lean percentage and reduction in sebum percentage. As a result, BQ had higher L45min, lower cooking scores, and lower drip loss. In addition, the loin muscle area, body length, and sebum percentage were significantly higher in 90 and 100 kg animals. Cooking loss showed a significant increase at 80 kg, and marbling increased significantly from 90 kg. Conclusion The results of this study suggest that QingYu pigs exhibit excellent reproductive properties and heritability of these traits. Crossing with Berkshire is an efficient strategy to improve the carcass and meat quality of QingYu pigs for commercial operations. Furthermore, it appears as though the optimal slaughter weight of BQ pigs is at approximately 90 kg.

Abstract Background Cancer cells undergo global reprogramming of cellular metabolism to satisfy demands of energy and biomass during proliferation and metastasis. Computational modeling of genome-scale metabolic models is an effective approach for designing new therapeutics targeting dysregulated cancer metabolism by identifying metabolic enzymes crucial for satisfying metabolic goals of cancer cells, but nearly all previous studies neglect the existence of metabolic demands other than biomass synthesis and trade-offs between these contradicting metabolic demands. It is thus necessary to develop computational models covering multiple metabolic objectives to study cancer metabolism and identify novel metabolic targets. Methods We developed a multi-objective optimization model for cancer cell metabolism at genome-scale and an integrated, data-driven workflow for analyzing the Pareto optimality of this model in achieving multiple metabolic goals and identifying metabolic enzymes crucial for maintaining cancer-associated metabolic phenotypes. Using this workflow, we constructed cell line-specific models for a panel of cancer cell lines and identified lists of metabolic targets promoting or suppressing cancer cell proliferation or the Warburg Effect. The targets were then validated using knockdown and over-expression experiments in cultured cancer cell lines. Results We found that the multi-objective optimization model correctly predicted phenotypes including cell growth rates, essentiality of metabolic genes and cell line specific sensitivities to metabolic perturbations. To our surprise, metabolic enzymes promoting proliferation substantially overlapped with those suppressing the Warburg Effect, suggesting that simply targeting the overlapping enzymes may lead to complicated outcomes. We also identified lists of metabolic enzymes important for maintaining rapid proliferation or high Warburg Effect while having little effect on the other. The importance of these enzymes in cancer metabolism predicted by the model was validated by their association with cancer patient survival and knockdown and overexpression experiments in a variety of cancer cell lines. Conclusions These results confirm this multi-objective optimization model as a novel and effective approach for studying trade-off between metabolic demands of cancer cells and identifying cancer-associated metabolic vulnerabilities, and suggest novel metabolic targets for cancer treatment. Graphical abstract

Objective: The relationships between body fat distribution, the adipokine adipsin and metabolic risks were assessed in patients with adult growth hormone deficiency (AGHD) before and after growth hormone (GH) treatment. Methods: Sixty newly diagnosed AGHD patients were included in our study, 24 of whom were evaluated after at least one year of GH treatment. Anthropometric parameters, glucolipid metabolism and the adipokine adipsin were measured. Visceral adipose tissue (VAT) and body composition were evaluated using a dual-energy X-ray-absorptiometry (DXA) scanner. Results: At baseline, the higher VAT group had worse glucolipid metabolism parameters. Basal GH was negatively associated with VAT (r=-0.277, p = 0.045), while minimal correlations were found with fat mass depots, such as limbs and trunk fat (all p > 0.05). Adipsin was correlated with total body fat (r = 0.543, p < 0.001), VAT (r = 0.563, p < 0.001) and insulin resistance (r = 0.353, p = 0.006). The effect of GH administration on fat distribution was mainly reflected in the reduction in VAT. Partial improvements were found in lipid profiles, including increased high-density lipoprotein (HDL) and decreases in triglycerides (TGs) and lipoprotein(a), while glucose metabolism showed little change. The adipsin level also decreased significantly. The best predictors of VAT at baseline were trunk fat and IGF-I, and after treatment, VAT was predicted by decreased adipsin and an increase in lean mass. Conclusions: (1) VAT is an important metabolic risk factor for AGHD patients. (2) GH treatment decreased body fat predominantly in the visceral and central fat depots. (3) The lipid profiles partially improved after treatment, while glucose metabolism showed little change.

We have researched a U-shape structure that consists of three vertical cavities coupled with bus wave-guide. The theoretical results based on the coupled mode theory are consistent with simulation results. We demonstrate that the interaction among two bright and one dark modes lead to dual plasmon induced transparency. Meanwhile, it is found that the lateral displacement S plays an important role in the transmission property, and the transmission dip with different transmittance in various lateral displacement S has been explained theoretically. Moreover, the nano sensor has a sensitivity of 1225 nm shift per refractive index unit, and the figure of merit is up to 62.5. The proposed structure has the advantages of simple and compact structure, easy fabrication, and the ultra-compact structure holds great potential to the control of light in highly integrated optical circuits and nano sensor.

Abstract The aim of this study was to investigate the association of sarcopenia and diabetic foot disease (DFD) in a cross-sectional study. Body composition was assessed using dual-energy X-ray-absorptiometry (DXA) among 1105 patients with type 2 diabetes (120 patients with newly diagnosed DFD [DFD duration less than 3 months]). Severity of DFD was assessed, referring to foot ulcers, Wagner grade and the percentage of amputation. Skeletal muscle index (SMI) was calculated, and sarcopenia was defined as SMI less than 7.0 kg/m2 (in men) or 5.4 kg/m2 (in women). SMI was significantly decreased in patients with DFD compared to patients without (6.79 ± 1.20 vs. 7.21 ± 1.05 kg/m2, P

Objective Qingyu pig, a Chinese indigenous pig breed, exhibits two types of coat colour phenotypes, including pure black and white with black spotting respectively. Melanocortin receptor 1 (MC1R) and agouti signaling protein (ASIP) are two widely reported pivotal genes that significantly affect the regulation of coat colour. The objectives of this study were to investigate whether the polymorphisms of these two genes are associated with coat colour and analyze the molecular mechanism of the coat colour separation in Qingyu pig. Methods We studied the phenotype segregation and used polymerase chain reaction amplification and Sanger sequencing to investigate the polymorphism of MC1R and ASIP in 121 Qingyu pigs, consisting of 115 black and 6 white with black spotted pigs. Results Coat colour of Qingyu pig is associated with the polymorphisms of MC1R but not ASIP. We only found 2 haplotypes, EQY and Eqy, based on the 13 observed mutations from MC1R gene. Among which, Eqy presented a recessive inheritance mode in black spotted Qingyu pigs. Further analysis revealed a g.462–463CC insertion that caused a frameshift mutation and a premature stop codon, thus changed the first transmembrane domain completely and lost the remaining six transmembrane domains. Altogether, our results strongly support that the variety of Qingyu pig’s coat colour is related to MC1R. Conclusion Our findings indicated that black coat colour in Qingyu pig was dominant to white with black spotted phenotype and MC1R gene polymorphism was associated with coat colour separation in Qingyu pig.

There is a large amount of backfilled earth on both sides of the wall and the top of the lower wall of the Daning Reservoir’s cutoff wall, which is greatly disturbed by the project, and the safety of the cutoff wall needs to be evaluated. Based on the deformation law and stress condition of rigid cutoff wall during construction, according to the connection characteristics of rigid cutoff wall and plastic cutoff wall structure, the stress analysis of rigid cutoff wall is carried out by using field measurement data, so as to deduce the deformation law of plastic cutoff wall underneath, and evaluate the safety of plastic cutoff wall. The results show that the plastic cutoff wall is mainly affected by compressive stress, and the maximum compressive stress is far less than the allowable compressive stress, which indicates that the plastic cutoff wall is safe and stable during the whole construction period, although it is affected by construction and rigid cutoff wall.

While the skin microbiome has been shown to play important roles in health and disease in several species, the effects of altitude on the skin microbiome and how high-altitude skin microbiomes may be associated with health and disease states remains largely unknown. Using 16S rRNA marker gene sequencing, we characterized the skin microbiomes of people from two racial groups (the Tibetans and the Hans) and of three local pig breeds (Tibetan pig, Rongchang pig, and Qingyu pig) at high and low altitudes. The skin microbial communities of low-altitude pigs and humans were distinct from those of high-altitude pigs and humans, with five bacterial taxa (Arthrobacter, Paenibacillus, Carnobacterium, and two unclassified genera in families Cellulomonadaceae and Xanthomonadaceae) consistently enriched in both pigs and humans at high altitude. Alpha diversity was also significantly lower in skin samples collected from individuals living at high altitude compared to individuals at low altitude. Several of the taxa unique to high-altitude humans and pigs are known extremophiles adapted to harsh environments such as those found at high altitude. Altogether our data reveal that altitude has a significant effect on the skin microbiome of pigs and humans.

The cellphone based localization system for search and rescue in complex high density ruins has attracted a great interest in recent years, where the radio channel characteristics are critical for design and development of such a system. This paper presents a spatial smoothing estimation via rotational invariance technique (SS-ESPRIT) for radio channel characterization of high density ruins. The radio propagations at three typical mobile communication bands (0.9, 1.8, and 2 GHz) are investigated in two different scenarios. Channel parameters, such as arrival time, delays, and complex amplitudes, are statistically analyzed. Furthermore, a channel simulator is built based on these statistics. By comparison analysis of average excess delay and delay spread, the validation results show a good agreement between the measurements and channel modeling results.

Previously, we identified the genetic variant -241 (-/G) (rs11453459) in the PP2A-Aα gene (PPP2R1A) promoter and demonstrated that this variant influences the DNA-binding affinity of nuclear factor-kappa B (NF-κB). In this study, we further confirmed that the transcriptional activity of PPP2R1A may be regulated by NF-κB through the functional genetic variant -241 (-/G). Moreover, we also demonstrated that the methylation status of CpG islands in the promoter of PPP2R1A influences the activity of this gene promoter. Few studies have examined the role of this -241 (-/G) variant in genetic or epigenetic regulation in hepatocellular carcinoma (HCC). To investigate whether this functional variant in the PPP2R1A promoter is associated with the risk of HCC and confirm the function of the -241 (-/G) variant in the HCC population, we conducted a case-control study involving 251 HCC cases and 252 cancer-free controls from a Han population in southern China. Compared with the -241 (--) homozygote, the heterozygous -241 (-G) genotype (adjusted OR = 0.32, 95% confidence interval (CI) = 0.17-0.58, P

Realizing a multifunctional integrated photonic platform is one of the goals for future optical information processing, which usually requires large size to realize due to multiple integration challenges. Here, we realize a multifunctional integrated photonic platform with ultracompact footprint based on inverse design. The photonic platform is compact with 86 inverse designed-fixed couplers and 91 phase shifters. The footprint of each coupler is 4 µm by 2 µm, while the whole photonic platform is 3 mm by 0.2 mm--one order of magnitude smaller than previous designs. One-dimensional Floquet Su-Schrieffer-Heeger model and Aubry-André-Harper model are performed with measured fidelities of 97.90 (±0.52) % and 99.34 (±0.44) %, respectively. We also demonstrate a handwritten digits classification task with the test accuracy of 87% using on-chip training. Moreover, the scalability of this platform has been proved by demonstrating more complex computing tasks. This work provides an effective method to realize an ultrasmall integrated photonic platform. [ABSTRACT FROM AUTHOR]

Objectives: The aims of this study were to develop and validate 2 simple scores for stratification of the risks of (1) any fragility (AF) and (2) major osteoporotic fracture (MOF) in type 2 diabetes (T2D) patients; we also compared the performance of these scores with that of the Fracture Risk Assessment Tool (FRAX) and its adjustments. Design and methods: In this longitudinal cohort study, 1855 patients with T2D were enrolled from January 2015 to August 2019. Cox proportional hazard regression was used to model the 5-year risk of AF and MOF. These scores were internally validated using a bootstrap resampling method of 1000. Results: During a median follow-up of 5 years, 119 (6.42%) cases of AF and 92 (4.96%) cases of MOFs were identified. Both the concordance index (C-index) and calibration plots indicated improved identification performance using the newly established scores. Furthermore, these scores also showed improved outcomes regarding the decision curve analysis (DCA) and area under the curve (AUC) compared to the widely used FRAX and its derivatives. More importantly, these scores successfully separated T2D patients into risk groups according to significant differences in fracture incidence. Conclusions: These novel scores enable simple and reliable fracture risk stratification in T2D patients. Future work is needed to validate these findings in external cohort(s). [ABSTRACT FROM AUTHOR]