scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding.

Single-cell proteomics sequencing technology sheds light on protein-protein interactions, posttranslational modifications and proteoform dynamics in the cell. However, the uncertainty estimation for peptide quantification, data missingness, batch effects and high noise hinder the analysis of single-cell proteomic data. It is important to solve this set of tangled problems together, but the existing methods tailored for single-cell transcriptomes cannot fully address this task. Here we propose a versatile framework designed for single-cell proteomics data analysis called scPROTEIN, which consists of peptide uncertainty estimation based on a multitask heteroscedastic regression model and cell embedding generation based on graph contrastive learning. scPROTEIN can estimate the uncertainty of peptide quantification, denoise protein data, remove batch effects and encode single-cell proteomic-specific embeddings in a unified framework. We demonstrate that scPROTEIN is efficient for cell clustering, batch correction, cell type annotation, clinical analysis and spatially resolved proteomic data exploration.

Early cancer detection from genome-wide cell-free DNA fragmentation via shuffled frog leaping algorithm and support vector machine.

MOTIVATION: Early cancer detection is significant for patient mortality rate reduction. Although machine learning has been widely employed in that context, there are still deficiencies. In this work, we studied different machine learning algorithms for early cancer detection and proposed an Adaptive Support Vector Machine (ASVM) method by synergizing Shuffled Frog Leaping Algorithm and Support Vector Machine (SVM) in this study. RESULTS: Since ASVM regulates SVM for parameter adaption based on data characteristics, the experimental results reflected the robust generalization capability of ASVM on different datasets under different settings; for instance, ASVM can enhance the sensitivity by over 10% for early cancer detection compared with SVM. Besides, our proposed ASVM outperformed Grid Search + SVM and Random Search + SVM by significant margins in terms of the area under the ROC curve (AUC) (0.938 versus 0.922 versus 0.921). AVAILABILITY AND IMPLEMENTATION: The proposed algorithm and dataset are available at https://github.com/ElaineLIU-920/ASVM-for-Early-Cancer-Detection. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Interleukin 18 and cognitive impairment in first episode and drug naïve schizophrenia versus healthy controls.

Alterations in the inflammatory and immune systems have been documented to occur from the earliest stages of schizophrenia, and have been associated with neurodevelopmental changes. Cognitive impairment is a core feature in the pathology of schizophrenia, and recent studies showed a significant increase in serum IL-18 in schizophrenia, and a putative role of IL-18 in neuroprogression and thus neurocognitive defects. The purpose of this study was to examine the association of IL-18 with cognitive deficits in schizophrenia. We recruited 77 first episode and drug naïve schizophrenic patients and 75 healthy control subjects and examined the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and serum IL-18 in both groups. Schizophrenic symptoms were assessed using the positive and negative syndrome scale (PANSS). We found that IL-18 levels were non-significantly higher in patients than controls (206.0±92.9 pg/ml vs 193.2±41.8 pg/ml, p=0.28). Cognitive scores on the RBANS and nearly all of its five subscales (all p<0.05) except for the Visuospatial/Constructional index (p>0.05) were significantly lower in schizophrenic patients than normal controls. For the patients, IL-18 was positively associated with the Visuospatial/Constructional domain of cognitive deficits in schizophrenia. Our findings suggest that cognitive deficits occur during the acute stage of a schizophrenic episode, and IL-18 may be involved in Visuospatial/Constructional deficits of these patients.

Flame Retardancy of Nylon 6 Fibers: A Review.

As synthetic fibers with superior performances, nylon 6 fibers are widely used in many fields. Due to the potential fire hazard caused by flammability, the study of the flame retardancy of nylon 6 fibers has been attracting more and more attention. The review has summarized the present research status of flame-retarded nylon 6 fibers from three aspects: intrinsic flame-retarded nylon 6, nylon 6 composites, and surface strategies of nylon 6 fibers/fabrics. The current main focus is still how to balance the application performances, flame retardancy, and production cost. Moreover, melt dripping during combustion remains a key challenge for nylon 6 fibers, and the further developing trend is to study novel flame retardants and new flame-retardancy technologies for nylon 6 fibers.

Lead-Free Textured Ceramics with Ultrahigh Piezoelectric Properties by Synergistic Design.

Lead-free ceramics with superior piezoelectric performance are highly desirable in various electromechanical applications. Unfortunately, it is still challenging to achieve significantly enhanced piezoelectricity without sacrificing the Curie temperature (Tc) in current BaTiO3-based ceramics. To address this issue, a synergistic design strategy of integrating crystallographic texture, multiphase coexistence, and doping engineering is proposed here. Highly [001]c-textured (Ba0.95Ca0.05)(Ti0.92Zr0.06Sn0.02)O3 ceramics are synthesized through Li-related liquid-phase-assisted templated grain growth, with improved grain orientation quality (f of ∼96% and r of ∼0.16) achieved at substantially reduced texture temperatures. Encouragingly, ultrahigh comprehensive piezoelectric properties, i.e., piezoelectric coefficient d33 of ∼820 pC N-1, electrostrain Smax/Emax of ∼2040 pm V-1, and figure of merit d33 × g33 of ∼23.5 × 10-12 m2 N-1, are simultaneously obtained without sacrificing Tc, which are also about 2.3, 2.4, and 4.3 times as high as those of non-textured counterpart, respectively. On the basis of the experiments and theoretical modeling, the outstanding piezoelectric performance is attributed to more effective exploration of property anisotropy and easier polarization rotation/extension, owing to improved grain orientation quality, dissolution of templates into oriented grains, coexisting R + O + T phases, and domain miniaturization. This work provides important guidelines for developing novel ceramics with outstanding piezoelectric properties and can largely expand application fields of textured BaTiO3-based ceramics into high-performance and multilayer electronic devices.

Lead zirconate titanate ceramics with aligned crystallite grains.

The piezoelectric properties of lead zirconate titanate [Pb(Zr,Ti)O3 or PZT] ceramics could be enhanced by fabricating textured ceramics that would align the crystal grains along specific orientations. We present a seed-passivated texturing process to fabricate textured PZT ceramics by using newly developed Ba(Zr,Ti)O3 microplatelet templates. This process not only ensures the template-induced grain growth in titanium-rich PZT layers but also facilitates desired composition through interlayer diffusion of zirconium and titanium. We successfully prepared textured PZT ceramics with outstanding properties, including Curie temperatures of 360°C, piezoelectric coefficients d33 of 760 picocoulombs per newton and g33 of 100 millivolt meters per newton, and electromechanical couplings k33 of 0.85. This study addresses the challenge of fabricating textured rhombohedral PZT ceramics by suppressing the otherwise severe chemical reaction between PZT powder and titanate templates.

Enhancing the Temperature Stability of 0.42PNN-0.21PZ-0.37PT Ceramics through Texture Engineering.

Although the MPB composition 0.42PNN-0.21PZ-0.37PT ceramic has high piezoelectric properties, its temperature stability at room temperature is rather poor due to the low phase-transition temperature. By texture engineering using BaTiO3 (BT) as the template, the temperature stability of this material can be greatly improved. In the temperature range from room temperature up to 140 °C, the high effective piezoelectric strain constant d33* of 0.42PNN-0.21PZ-0.37PT-3BT only changed by 4.9% from 1278 to 1215 pm/V, while the d33* of the nontextured counterpart changed by 46.7% from the room temperature value of 920 pm/V with the maximum deviation to 1350 pm/V at 80 °C. In addition, the textured ceramic has higher piezoelectric properties, lower dielectric loss, and slightly higher coercive field. The room-temperature figure-of-merit d33 × g33 for PNN-PZT-2BT is increased by as much as 42% compared with the nontextured counterpart. Our results demonstrated that texture engineering is an effective way to improve the temperature stability of the MPB composition piezoceramics.

Mini-review: Recent advances in post-translational modification site prediction based on deep learning.

Post-translational modifications (PTMs) are closely linked to numerous diseases, playing a significant role in regulating protein structures, activities, and functions. Therefore, the identification of PTMs is crucial for understanding the mechanisms of cell biology and diseases therapy. Compared to traditional machine learning methods, the deep learning approaches for PTM prediction provide accurate and rapid screening, guiding the downstream wet experiments to leverage the screened information for focused studies. In this paper, we reviewed the recent works in deep learning to identify phosphorylation, acetylation, ubiquitination, and other PTM types. In addition, we summarized PTM databases and discussed future directions with critical insights.

Epistasis Analysis: Classification Through Machine Learning Methods.

Complex disease is different from Mendelian disorders. Its development usually involves the interaction of multiple genes or the interaction between genes and the environment (i.e. epistasis). Although the high-throughput sequencing technologies for complex diseases have produced a large amount of data, it is extremely difficult to analyze the data due to the high feature dimension and the combination in the epistasis analysis. In this work, we introduce machine learning methods to effectively reduce the gene dimensionality, retain the key epistatic effects, and effectively characterize the relationship between epistatic effects and complex diseases.

Development and validation of a nomogram for prediction of the risk of positive hidden blood loss in the perioperative period of single-level thoracolumbar burst fracture.

BACKGROUND: This study aimed to develop and validate an individualized nomogram to predict the risk of positive hidden blood loss (HBL) in patients with single-level thoracolumbar burst fracture (TBF) during the perioperative period. METHODS: We conducted a retrospective investigation including 150 consecutive patients with TBL, and the corresponding patient data was extracted from March 2013 to March 2019. The independent risk factors for positive HBL were screened using univariate and multivariate logistic regression analyses. According to published literature and clinical experience, a series of variables were selected to develop a nomogram prediction model for positive HBL. The area under the receiver operating characteristic curves (AUC), C-index, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the prediction model. Bootstrapping validation was performed to evaluate the performance of the model. RESULTS: Among the 150 consecutive patients, 62 patients were positive for HBL (38.0%). The multivariate logistic regression analysis showed that the six risk factors of age, length of surgical incision, duration of operation, percentage of vertebral height restoration (P1%), preoperative total cholesterol, and preoperative fibrinogen were independent risk factors of positive HBL. The C-index was 0.831 (95% CI 0.740-0.889) and 0.845 in bootstrapping validation, respectively. The calibration curve showed that the predicted probability of the model was consistent with the actual probability. Decision curve analysis (DCA) showed that the nomogram had clinical utility. CONCLUSION: Overall, we explored the relationship between the positive HBL requirement and predictors. The individualized prediction model for patients with single-level TBF can accurately assess the risk of positive HBL and facilitate clinical decision making. However, external validation will be needed in the future.

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey.

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

40-Hz Blue Light Changes Hippocampal Activation and Functional Connectivity Underlying Recognition Memory.

Research on light modulation has typically examined the wavelength, intensity, and exposure time of light, and measured rhythm, sleep, and cognitive ability to evaluate the regulatory effects of light variables on physiological and cognitive functions. Although the frequency of light is one of the main dimensions of light, few studies have attempted to manipulate it to test the effect on brain activation and performance. Recently, 40-Hz light stimulation has been proven to significantly alleviate deficits in gamma oscillation of the hippocampus caused by Alzheimer's disease. Although this oscillation is one of the key functional characteristics of performing memory tasks in healthy people, there is no evidence that 40-Hz blue light exposure can effectively regulate brain activities related to complex cognitive tasks. In the current study, we examined the difference in the effects of 40-Hz light or 0-Hz light exposure on brain activation and functional connectivity during a recognition memory task. Through joint augmentation of visual area activation, 40-Hz light enhanced brain areas mostly in the limbic system that are related to memory, such as the hippocampus and thalamus. Conversely, 0-Hz light enhanced brain areas mostly in the prefrontal cortex. Additionally, functional connection analysis, with the hippocampus as the seed point, showed that 40-Hz light enhanced connection with the superior parietal lobe and reduced the connection with the default network. These results indicate that light at a frequency of 40 Hz can change the activity and functional connection of memory-related core brain areas. They also indicate that in the use of light to regulate cognitive functions, its frequency characteristics merit attention.

Silencing of RGS2 enhances hippocampal neuron regeneration and rescues depression-like behavioral impairments through activation of cAMP pathway.

Depression is one of the most common mental disorders with an increasing incidence. However, factors involved in depression are so complex, thus it is difficult to find effective strategies to reverse the impairments. This study aims to verify the role of regulator of G protein signaling 2 (RGS2) in the mouse mode of unpredictable mild stress-induced depression-like behaviors. Knockdown of RGS2 was achieved by transfection of siRNA-RGS2 in mouse hippocampal (HT-22) cells in vitro and injection of recombinant adenovirus expressing siRNA-RGS2 in mice in vivo. An aberrant high expression of RGS2 was found in mice with depression-like behaviors through immunohistochemical analysis. Silencing of RGS2 or Forskolin (activator of cAMP pathway) developed sweet water consumption, reduced inflammation and oxidative stress injury, and attenuated cognitive impairment and neuronal damage in mice with depression-like behaviors. Furthermore, regeneration was enhanced and apoptosis was repressed in mouse hippocampal neurons in the presence of RGS2 knockdown and Forskolin. Mechanistic studies indicated that silencing of RGS2 promoted the activation of cAMP pathway, thus rescuing depression-like behaviors of mice. Collectively, our study uncovered the role of RGS2-dependent cAMP pathway in regulation of cognitive impairment and hippocampal neuron regeneration in depression-like behaviors of mice, which may be a potential therapeutic target for impairments and symptoms associated with depression.

Grain-Oriented Ferroelectric Ceramics with Single-Crystal-like Piezoelectric Properties and Low Texture Temperature.

High-performance piezoelectrics are pivotal to various electronic applications including multilayer actuators, sensors, and energy harvesters. Despite the presence of high Lotgering factor F001, two key limitations to today's relaxor-PbTiO3 textured ceramics are low piezoelectric properties relative to single crystals and high texture temperature. In this work, Pb(Yb1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-PbTiO3 (PYN-PMN-PT) textured ceramics with F001 ∼ 99% were synthesized at only 975 °C through liquid-phase-assisted templated grain growth, where of particular significance is that single-crystal properties, i.e., very large electrostrain Smax/Emax ∼ 1830 pm V-1, giant piezoelectric figure of merit d33 × g33 ∼ 61.3 × 10-12 m2 N-1, high electromechanical coupling k33 ∼ 0.90, and Curie temperature Tc ∼ 205 °C, were simultaneously achieved. Especially, the Smax/Emax and d33 × g33 values correspond to ∼180% enhancement as compared to the regularly 1200 °C-textured ceramics with F001 ∼ 96%, representing the highest values ever reported on piezoceramics. Phase-field simulation revealed that grain misorientation has a stronger influence on piezoelectricity than texture fraction. The ultrahigh piezoelectric response achieved here is mainly attributed to effective control of grain orientation features and domain miniaturization. This work provides important guidelines for developing novel ceramics with significantly enhanced functional properties and low synthesis temperature in the future and can also greatly expand application fields of piezoceramics to high-performance, miniaturized electronic devices with multilayer structures.

Adlay starch-gluten composite gel: Effects of adlay starch on rheological and structural properties of gluten gel to molecular and physico-chemical characteristics.

Effects of adlay starch on the rheological and conformational changes in wheat gluten gel were investigated in this study. Rheological measurement showed that adlay starch-gluten composite gels exhibited higher storage modulus G' and loss modulus G″ compared with pure gluten gels. This result was also confirmed through morphological analysis. As the addition of adlay starch increased from 0% to 40%, the surface hydrophobicity of gluten protein gel decreased from 16,660 to 11,931 and the free thiol content increased from 3.11 to 4.30 µmol/g. In addition, the ß-sheet structure in the gluten protein gel increased at the expense of the α-helical structure with increasing adlay starch fraction. This study revealed that besides acting as an inert filler, adlay starch could participate in hydrogen bonding and induce the enhancement of hydrophobic interaction to modify gluten protein association, altering the rheological and structural properties of gluten protein gels.

Correlations of PTEN genetic polymorphisms with the risk of depression and depressive symptoms in a Chinese population.

OBJECTIVE: This study aimed to investigate the correlations of three common single nucleotide polymorphisms (SNPs) in the PTEN gene (rs701848 T>C, rs2735343 G>C and rs112025902 A>T) with the risk of depression and depressive symptoms in a Chinese population. METHODS: From July 2011 to June 2013, a total of 384 patients with depression and 400 healthy individuals were included in this study. These SNPs in the PTEN gene were detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct sequencing. The Hamilton Depression Rating Scale (HAMD) was used to evaluate the severity of depression. RESULTS: The C allele of rs701848, the C allele of rs2735343 and the T allele of rs112025902 were associated with an increased risk of depression (odds ratio [OR]=3.814, 95% CI: 3.093-4.703, P<0.001; OR=2.642, 95% CI: 2.152-3.242, P<0.001; OR=2.882, 95% CI: 2.347-3.539, P<0.001; respectively). Depression patients carrying C allele (TC+CC) of rs701848 and carrying T allele (AT+TT) of rs112025902 had higher HAMD total scores and HAMD anxiety factor scores than those carrying TT genotype of rs701848 and carrying AA genotype of rs112025902 (all P<0.05). Furthermore, depression patients carrying C allele (GC+CC) of rs2735343 had lower HAMD total scores and HAMD factors associated with depression scores than those carrying GG genotype (both P<0.05). Logistic regression analysis revealed that rs701848, rs2735343 and rs112025902 polymorphisms in the PTEN gene may be independent risk factors of depression (relative risk [RR]=1.807, 95% CI=1.023-3.193, P=0.042; RR=1.759, 95% CI=1.033-2.995, P=0.038; RR=1.646, 95% CI=1.018-2.663, P=0.042; respectively). CONCLUSION: Our findings provide evidence that rs701848, rs2735343 and rs112025902 polymorphisms in the PTEN gene may be correlated with the risk of depression and depressive symptoms in the Chinese population.

Prevalence of tardive dyskinesia in chronic male inpatients with schizophrenia on long-term clozapine versus typical antipsychotics.

This study aimed to examine the prevalence and clinical associated variables of tardive dyskinesia (TD) in a large sample of Chinese inpatients with schizophrenia on long-term treatment with clozapine versus typical antipsychotics. A total of 584 male inpatients with schizophrenia on long-term clozapine (n=341) or typical antipsychotic (n=243) treatment were evaluated using the Abnormal Involuntary Movement Scale (AIMS). The patient's psychopathology was assessed using the Positive and Negative Syndrome Scale. The overall prevalence of TD was 44.5%, with rates of 48.7% in the clozapine group and 38.7% in the typical antipsychotic group (P=0.017). The AIMS score was significantly lower in typical than in clozapine groups (P<0.005). A multiple regression analysis showed that the following variables were significantly associated with the AIMS score: clozapine versus typical medication (P=0.008), Positive and Negative Syndrome Scale negative subscore (P=0.017), and age (P=0.04). There are significant differences in the prevalence and clinical correlates of TD in schizophrenia treated with clozapine versus typical antipsychotics.

Gender differences in socio-demographic and clinical characteristics of methamphetamine inpatients in a Chinese population.

BACKGROUND: Over the past two decades, China has experienced a dramatic increase in methamphetamine (MA) abuse. This study examined gender-specific socio-demographic and clinical characteristics of MA use among Han Chinese, which has previously received little systematic study. METHODS: This analysis described MA-related socio-demographic and clinical characteristics in a broad cross-sectional sample (n=1464; male/female=1185/279), and examined differences between males and females in MA use history, MA initiation, MA-related subjective feelings and behaviors, and withdrawal symptoms. RESULTS: Most MA abusers (about 72%) were young (in their 20s or 30s), with women being 5 years younger than men on average. More males (33.2%) were married than females (21.9%). The average body mass index (BMI) was significantly lower in this MA abuser sample compared to the age-matched healthy controls. Moreover, the BMI of females was significantly lower than that of males. The laboratory tests showed that the blood levels of glucose, cholesterol and triglyceride were all significantly higher in males than females. Females used MA at a younger age compared to males. The most frequent route of MA use was smoking (90.9%). Males were more likely to use another drug, and more likely to be hospitalized. However, many characteristics and behaviors of MA use are similar for males and females, including the route, the dose and duration of MA use, and relapse status. CONCLUSION: Although there were some male-female similarities in MA use parameters, significant differences do exist that may have implications for gender-specific research as well as for prevention and treatment strategies.

Elevated plasma superoxide dismutase in first-episode and drug naive patients with schizophrenia: inverse association with positive symptoms.

Excessive free radical production or oxidative stress may be involved in the pathophysiology of schizophrenia as evidenced by increased superoxide dismutase (SOD) activities, a critical enzyme in the detoxification of superoxide radicals. This study compared plasma SOD activities in 78 never-medicated first-episode and 100 medicated chronic schizophrenia patients to 100 healthy control subjects and correlated these SOD activities with the Positive and Negative Syndrome Scale (PANSS) among the schizophrenic patients. We found that both first-episode and chronic patients had significantly increased plasma SOD activities compared to controls, and that chronic schizophrenic patients on antipsychotic medication had significantly higher SOD activities than first episode schizophrenic patients. Plasma SOD activities were also negatively correlated with positive symptoms of schizophrenia, but only in first-episode patients. Thus, oxidative stress appears to be greater in first episode schizophrenic patients with fewer positive symptoms and may become greater as schizophrenia becomes more chronic, although we cannot exclude the possibility that chronic antipsychotic treatment may increase SOD activities and presumed oxidative stress in schizophrenia.