Binding of single/double stranded ct-DNA with graphene oxide­silver nanocomposites in vitro: A multispectroscopic approach.

The fundamental binding of single-stranded (ssDNA) and double-stranded DNA (dsDNA) with graphene oxide-Ag nanocomposites (GO-AgNCPs) has been systematically investigated by multi spectroscopic methods, i.e. ultraviolet-visible (UV-vis) absorption, fluorescence spectroscopy, and circular dichroism (CD). The experimental and theoretical results demonstrate that both ssDNA and dsDNA can be adsorbed onto the GO-AgNCPs surface. All of the evidence indicated that there were relatively strong binding of ssDNA/dsDNA with GO-AgNCPs. The article compares the differences in binding between the two types of DNA and the nanomaterials using spectroscopic and thermodynamic data. UV-vis absorption spectroscopy experiments indicate that the characteristic absorbance intensity of both ss DNA and ds DNA increases, but the rate of change in absorbance is different. The fluorescence results revealed that ss/dsDNA could interact with the GO-AgNCPs surface, in spite of the different binding affinities. The Ka value of ssDNA binding with GO-AgNCPs is greater than that of dsDNA at each constant temperature, indicating that the affinity of dsDNA toward GO-AgNCPs is comparatively weak. Molecular docking studies have corroborated the mentioned experimental results. The calculated thermodynamic parameters showed that the binding process was thermodynamically spontaneous, van der Waals force and hydrogen bonding played predominant roles in the binding process. The mechanism of ss/ds DNA binding with GO-AgNCPs was also investigated, and the results indicated that GO-AgNCPs directly binds to the minor groove of ss/ds DNA by replacing minor groove binders.

BioCoder: a benchmark for bioinformatics code generation with large language models.

SUMMARY: Pretrained large language models (LLMs) have significantly improved code generation. As these models scale up, there is an increasing need for the output to handle more intricate tasks and to be appropriately specialized to particular domains. Here, we target bioinformatics due to the amount of domain knowledge, algorithms, and data operations this discipline requires. We present BioCoder, a benchmark developed to evaluate LLMs in generating bioinformatics-specific code. BioCoder spans much of the field, covering cross-file dependencies, class declarations, and global variables. It incorporates 1026 Python functions and 1243 Java methods extracted from GitHub, along with 253 examples from the Rosalind Project, all pertaining to bioinformatics. Using topic modeling, we show that the overall coverage of the included code is representative of the full spectrum of bioinformatics calculations. BioCoder incorporates a fuzz-testing framework for evaluation. We have applied it to evaluate various models including InCoder, CodeGen, CodeGen2, SantaCoder, StarCoder, StarCoder+, InstructCodeT5+, GPT-3.5, and GPT-4. Furthermore, we fine-tuned one model (StarCoder), demonstrating that our training dataset can enhance the performance on our testing benchmark (by >15% in terms of Pass@K under certain prompt configurations and always >3%). The results highlight two key aspects of successful models: (i) Successful models accommodate a long prompt (>2600 tokens) with full context, including functional dependencies. (ii) They contain domain-specific knowledge of bioinformatics, beyond just general coding capability. This is evident from the performance gain of GPT-3.5/4 compared to the smaller models on our benchmark (50% versus up to 25%). AVAILABILITY AND IMPLEMENTATION: All datasets, benchmark, Docker images, and scripts required for testing are available at: https://github.com/gersteinlab/biocoder and https://biocoder-benchmark.github.io/.

Adverse effects of Microcystis aeruginosa exudates on the filtration, digestion, and reproduction organs of benthic bivalve Corbicula fluminea.

Cyanobacteria bloom and the secondary metabolites released by the microorganism are extremely harmful to aquatic animals, yet study on their adverse effects in zoobenthos is rare. Corbicula fluminea widely distributed in freshwater environment with algal blooms. It is a typical filter feeding zoobenthos that may be affected by the secondary metabolites of cyanobacteria due to its high filtering rate. In this study, C. fluminea was exposed to Microcystis aeruginosa exudates (MaE) for 96 h, which was obtained from 5 × 105 cells/mL and 2.5 × 106 cells/mL exponential stage M. aeruginosa culture solution that represented cyanobacteria cell density needs environmental risk precaution control and emergent control, respectively. The responses of C. fluminea critical organs to MaE were analyzed and evaluated based on histopathological sections, antitoxicity biomarkers, and organ function biomarkers. The results showed that all the organs underwent structural disorders, cell vacuolization, apoptosis, and necrosis, and the damage levels increased as MaE concentration increased. The detoxification and antioxidant defense systems biomarkers in each organ response to MaE exposure differently and the level of reaction improved when MaE concentration increased. The siphon rate and acetylcholinesterase activity showed that the filtration function decreased significantly as the MaE concentration increased. Increased activity of glutathione S-transferase and amylase in the digestive gland indicate that it is the major detoxification organ of C. fluminea. Increased vitellogenin concentration and enlarged oocytes in the gonad indicate that MaE may have an estrogenic effect on C. fluminea. This study demonstrates that cyanobacteria threat benthic bivalves by inducing oxidative stress, inhibiting filtering feeding system, and disturbing digestion system and reproduction potential of C. fluminea.

Estimating changes of forest carbon storage in China for 70 years (1949-2018).

In the realm of forest resource inventory and monitoring, stand-level biomass carbon models are especially crucial. In China, their importance is underscored as they form the bedrock for estimating national and international forest carbon storage. This study, based on the data from 52,700 permanent plots in the 9th National Forest Inventory (NFI) of China, was directed towards developing these models. After computing biomass and carbon storage per hectare using specific tree models for 34 species groups, we devised robust volume-derived biomass and carbon storage models for 20 forest types. The application of these models and historical data reveals notably a decline in China's forest carbon storage to 4.90Pg by the late 1970s due to aggressive forest exploitation. However, subsequent conservation and afforestation campaigns have affected a recovery, culminating in a storage of 8.69Pg by the 9th NFI. Over the past 40 years, China's forest carbon storage has surged by 3.79Pg, split between natural forests (2.25Pg) and planted forests (1.54Pg). In benchmarking against three pre-existing models, we discerned discernible biases, underscoring the need for larger modeling sample sizes. Overall, our models stand as a monumental stride in accurately gauging forest carbon storage fluctuations in China, both regionally and nationally.

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses.

As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training data in order to achieve state-of-the-art performance. The absence of trustworthy human supervision over the data collection process exposes organizations to security vulnerabilities; training data can be manipulated to control and degrade the downstream behaviors of learned models. The goal of this work is to systematically categorize and discuss a wide range of dataset vulnerabilities and exploits, approaches for defending against these threats, and an array of open problems in this space.

Competition-level code generation with AlphaCode.

Programming is a powerful and ubiquitous problem-solving tool. Systems that can assist programmers or even generate programs themselves could make programming more productive and accessible. Recent transformer-based neural network models show impressive code generation abilities yet still perform poorly on more complex tasks requiring problem-solving skills, such as competitive programming problems. Here, we introduce AlphaCode, a system for code generation that achieved an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform. AlphaCode solves problems by generating millions of diverse programs using specially trained transformer-based networks and then filtering and clustering those programs to a maximum of just 10 submissions. This result marks the first time an artificial intelligence system has performed competitively in programming competitions.

Heterogeneous logistic regression for estimation of subgroup effects on hypertension.

Personalized medicine has gained much attention in the past decades, and identifying the effects of factors is essential for personalized preventions and treatments. Hypertension is a major modifiable risk factor for cardiovascular disease and is influenced by complex factors. In order to decrease the incidence of hypertension effectively, the subjects should be divided into subgroups according to their characteristics. In this study, we proposed to use a heterogeneous logistic regression combined with a concave fusion penalty to analyze the population-based survey data, including common influencing factors of hypertension. The analytic steps include: (1) identifying the most important predictor; (2) estimating subgroup-based heterogeneous effects. In the present context of primary hypertension data, the modeling results showed that the calculated prediction accuracy under our method was greater than 99%, while zero under the classical logistic regression. The findings could provide a practical guide for further individualized measures implementation.

Elasticity measurements of ocular anterior and posterior segments using optical coherence elastography.

The changes of biomechanical properties, especially the elasticity of the ocular tissues, are closely related to some ophthalmic diseases. Currently, the ophthalmic optical coherence elastography (OCE) systems are dedicated either to the anterior segment or to the retina. The elasticity measurements of the whole eye remain challenging. Here we demonstrated an acoustic radiation force optical coherence elastography (ARF-OCE) method to quantify the elasticity of the cornea and the retina. The experiment results show that the Young's moduli of the cornea and the retina were 16.66 ± 6.51 kPa and 207.96 ± 4.75 kPa, respectively. Our method can measure the elasticity of the anterior segment and the posterior segment, and provides a powerful tool to enhance ophthalmology research.

E2A ablation enhances proportion of nodal-like cardiomyocytes in cardiac-specific differentiation of human embryonic stem cells.

BACKGROUND: Human sinoatrial cardiomyocytes are essential building blocks for cell therapies of conduction system disorders. However, current differentiation protocols for deriving nodal cardiomyocytes from human pluripotent stem cells (hPSCs) are very inefficient. METHODS: By employing the hPSCs to cardiomyocyte (CM) in vitro differentiation system and generating E2A-knockout hESCs using CRISPR/Cas9 gene editing technology, we analyze the functions of E2A in CM differentiation. FINDINGS: We found that knockout of the transcription factor E2A substantially increased the proportion of nodal-like cells in hESC-derived CMs. The E2A ablated CMs displayed smaller cell size, increased beating rates, weaker contractile force, and other functional characteristics similar to sinoatrial node (SAN) cells. Transcriptomic analyses indicated that ion channel-encoding genes were up-regulated in E2A ablated CMs. E2A directly bounded to the promoters of genes key to SAN development via conserved E-box motif, and promoted their expression. Unexpect enhanced activity of NOTCH pathway after E2A ablation could also facilate to induct ventricle workingtype CMs reprogramming into SAN-like cells. INTERPRETATION: Our study revealed a new role for E2A during directed cardiac differentiation of hESCs and may provide new clues for enhancing induction efficiency of SAN-like cardiomyocytes from hPSCs in the future. FUNDING: This work was supported by the NSFC (No.82070391, N.S.; No.81870175 and 81922006, P.L.), the National Key R&D Program of China (2018YFC2000202, N.S.; 2017YFA0103700, P.L.), the Haiju program of National Children's Medical Center EK1125180102, and Innovative research team of high-level local universities in Shanghai and a key laboratory program of the Education Commission of Shanghai Municipality (ZDSYS14005).

The Emerging Roles of the RNA Binding Protein QKI in Cardiovascular Development and Function.

RNA binding proteins (RBPs) have a broad biological and physiological function and are critical in regulating pre-mRNA posttranscriptional processing, intracellular migration, and mRNA stability. QKI, also known as Quaking, is a member of the signal transduction and activation of RNA (STAR) family, which also belongs to the heterogeneous nuclear ribonucleoprotein K- (hnRNP K-) homology domain protein family. There are three major alternatively spliced isoforms, QKI-5, QKI-6, and QKI-7, differing in carboxy-terminal domains. They share a common RNA binding property, but each isoform can regulate pre-mRNA splicing, transportation or stability differently in a unique cell type-specific manner. Previously, QKI has been known for its important role in contributing to neurological disorders. A series of recent work has further demonstrated that QKI has important roles in much broader biological systems, such as cardiovascular development, monocyte to macrophage differentiation, bone metabolism, and cancer progression. In this mini-review, we will focus on discussing the emerging roles of QKI in regulating cardiac and vascular development and function and its potential link to cardiovascular pathophysiology.

The Role of Cholesterol Homeostasis in Diabetic Kidney Disease.

Considerable evidence has proved that disturbed cholesterol metabolism played a crucial role in diabetic kidney disease. Besides, massive cholesterol depositions were found in intrinsic renal cells of diabetic kidney disease patients and animal models, causing cytotoxicity and affecting renal function. Statins could alleviate cholesterol depositions, podocyte injury, and microalbuminuria of diabetic kidney disease. In this review, we summarized the process of disturbed cholesterol metabolism and discussed how it induced kidney dysfunction in diabetic kidney disease.

QKI is a critical pre-mRNA alternative splicing regulator of cardiac myofibrillogenesis and contractile function.

The RNA-binding protein QKI belongs to the hnRNP K-homology domain protein family, a well-known regulator of pre-mRNA alternative splicing and is associated with several neurodevelopmental disorders. Qki is found highly expressed in developing and adult hearts. By employing the human embryonic stem cell (hESC) to cardiomyocyte differentiation system and generating QKI-deficient hESCs (hESCs-QKIdel) using CRISPR/Cas9 gene editing technology, we analyze the physiological role of QKI in cardiomyocyte differentiation, maturation, and contractile function. hESCs-QKIdel largely maintain normal pluripotency and normal differentiation potential for the generation of early cardiogenic progenitors, but they fail to transition into functional cardiomyocytes. In this work, by using a series of transcriptomic, cell and biochemical analyses, and the Qki-deficient mouse model, we demonstrate that QKI is indispensable to cardiac sarcomerogenesis and cardiac function through its regulation of alternative splicing in genes involved in Z-disc formation and contractile physiology, suggesting that QKI is associated with the pathogenesis of certain forms of cardiomyopathies.

Inhibition of Estrogen Sulfotransferase (SULT1E1/EST) Ameliorates Ischemic Acute Kidney Injury in Mice.

BACKGROUND: Studies have suggested that estrogens may protect mice from AKI. Estrogen sulfotransferase (SULT1E1, or EST) plays an important role in estrogen homeostasis by sulfonating and deactivating estrogens, but studies on the role of SULT1E1 in AKI are lacking. METHODS: We used the renal ischemia-reperfusion model to investigate the role of SULT1E1 in AKI. We subjected wild-type mice, Sult1e1 knockout mice, and Sult1e1 knockout mice with liver-specific reconstitution of SULT1E1 expression to bilateral renal ischemia-reperfusion or sham surgery, either in the absence or presence of gonadectomy. We assessed relevant biochemical, histologic, and gene expression markers of kidney injury. We also used wild-type mice treated with the SULT1E1 inhibitor triclosan to determine the effect of pharmacologic inhibition of SULT1E1 on AKI. RESULTS: AKI induced the expression of Sult1e1 in a tissue-specific and sex-specific manner. It induced expression of Sult1e1 in the liver in both male and female mice, but Sult1e1 induction in the kidney occurred only in male mice. Genetic knockout or pharmacologic inhibition of Sult1e1 protected mice of both sexes from AKI, independent of the presence of sex hormones. Instead, a gene profiling analysis indicated that the renoprotective effect was associated with increased vitamin D receptor signaling. Liver-specific transgenic reconstitution of SULT1E1 in Sult1e1 knockout mice abolished the protection in male mice but not in female mice, indicating that Sult1e1's effect on AKI was also tissue-specific and sex-specific. CONCLUSIONS: SULT1E1 appears to have a novel function in the pathogenesis of AKI. Our findings suggest that inhibitors of SULT1E1 might have therapeutic utility in the clinical management of AKI.

The SUMOylated METTL8 Induces R-loop and Tumorigenesis via m3C.

R-loops, three-stranded DNA-DNA:RNA hybrid structures, are best known for their deleterious effects on genome stability. The regulatory factors of this fundamental genetic structure remain unclear. Here, we reveal an epigenetic factor that controls R-loop stability. METTL8, a member of the methyltransferase-like protein family that methylates 3-methylcytidine (m3C), is a key factor in the R-loop regulating methyltransferase complex. Biochemical studies show that METTL8 forms a large SUMOylated nuclear RNA-binding protein complex (∼0.8 mega daltons) that contains well-reported R-loop related factors. Genetic ablation of METTL8 results in an overall reduction of R-loops in cells. Interaction assays indicated METTL8 binds to RNAs and is responsible for R-loop stability on selected gene regions. Our results demonstrate that the SUMOylated METTL8 promotes tumorigenesis by affecting genetic organization primarily in, or in close proximity to, the nucleolus and impacts the formation of regulatory R-loops through its methyltransferase activity on m3C.

Effects of SSRIs on peripheral inflammatory cytokines in patients with Generalized Anxiety Disorder.

BACKGROUND: Extensive research into psychoneuroimmunology has led to substantial advances in our understanding of the reciprocal interactions between the central nervous system and the immune system in neuropsychiatric disorders. To date, inflammation has been implicated in the pathogenesis of depression and anxiety. The immunomodulating effects of antidepressants on depression have been reported, however, there is no evidence of the similar effects of antidepressants on anxiety. The aim of the study was to investigate the effects of selective serotonin reuptake inhibitors (SSRIs) on peripheral inflammatory cytokines in patients with first episode generalized anxiety disorder (GAD). METHODS: A prospective cohort design was employed: 42 patients with first episode GAD were treated with either escitalopram or sertraline for 12 weeks. Anxiety was measured by the Generalized Anxiety Disorder Scale and the State Trait Anxiety Inventory, serum pro-inflammatory cytokine levels were measured by the enzyme-linked immunosorbent assay (ELISA), and CRP determined by an immunoturbidimetric method before and after SSRIs treatment RESULTS: Baseline levels of anxiety and pro-inflammatory cytokines including IL-1α, IL-6, IL-8, IL-12, IFN-γ, and CRP were significantly reduced after treatment of SSRIs (p < 0.05 in all cases). In addition, the change of anxiety measures co-vary with the change of peripheral cytokine levels (p < 0.05 in all cases). The regression model revealed that log transformed baseline levels of CRP and IL-6 predicted treatment response (p < 0.05 in both cases). CONCLUSIONS: This study is the first to investigate the effects of SSRIs on pro-inflammatory cytokines in patients with first episode GAD. The findings indicate moderate acute anti-inflammatory effects of SSRIs in GAD, and suggest that these anti-inflammatory effects may underlie anxiolytic effects of SSRIs. The study also indicates that serum levels of CRP and IL-6 may predict treatment response. However, data from randomized controlled trials is warranted to confirm these findings.

Ecological micro-expression recognition characteristics of young adults with subthreshold depression.

The micro-expression (ME) processing characteristics of patients with depression has been studied but has not been investigated in people with subthreshold depression. Based on this, by adopting the ecological MEs recognition paradigm, this study aimed to explore ME recognition in people with subthreshold depression. A 4 (background expression: happy, neutral, sad and fearful) × 4 (ME: happy, neutral, sad, and fearful) study was designed; two groups of participants (experimental group with subthreshold depression vs. healthy control group, 32 participants in each group) were asked to complete the ecological ME recognition task, and the corresponding accuracy (ACC) and reaction time (RT) were analyzed. Results: (1) Under different background conditions, recognizing happy MEs had the highest ACC and shortest RT. (2) There was no significant difference in the ACC and RT between experimental and control groups. (3)In different contexts, individuals with subthreshold depression tended to misjudge neutral, sad, and fearful MEs as happy, while neutral MEs were misjudged as sad and fearful. (4) The performance of individuals with subthreshold depression in the ecological ME recognition task were influenced by the type of ME; they showed highest ACC and shortest RT when recognizing happy MEs (vs. the other MEs). Conclusions: (1) The performance of individuals' ecological ME recognition were influenced by the background expression, and this embodied the need for ecological ME recognition. (2) Individuals with subthreshold depression showed normal ecological ME recognition ability. (3) In terms of misjudgment, individuals with subthreshold depression showed both positive and negative bias, when completing the ecological ME recognition task. (4) Compared with the other MEs, happy MEs showed an advantage recognition effect for individuals with subthreshold depression who completed the ecological ME recognition task.

Evaluation of the predictive value of high sensitivity C-reactive protein in pregnancy-induced hypertension syndrome.

Relationship between serum high sensitive C-reactive protein (hs-CRP) and pregnancy-induced hypertension syndrome (PIH) was investigated. One hundred and twenty patients with PIH treated in the First People's Hospital of Chengdu (60 cases of mild preeclampsia, 60 cases of severe preeclampsia) were enrolled in the study. The control group included 60 women with normal singleton pregnancy. Serum hs-CRP and microalbuminuria (mALB) levels were measured by an AU5800 automatic biochemical analyzer (Beckerman Coulter), and the risk factors were analyzed by ROC curve analysis. Patients with PIH had higher levels of serum hs-CRP and mALB than the control group (P<0.01). Serum hs-CRP and mALB levels in the severe preeclampsia group were significantly higher than those in the mild preeclampsia group (P<0.05). ROC curve analysis showed that hs-CRP was a factor of high-risk. Area under the curve was 0.943, and the 95% confidence interval was 0.848-0.974. Detection of serum hs-CRP in patients with PIH can provide references for the prediction of the severity of the disease, and higher level of hs-CRP indicates worse condition.

Peripheral proinflammatory cytokines in Chinese patients with generalised anxiety disorder.

BACKGROUND: Inflammatory responses and inflammatory cytokines have been implicated in the pathogenesis of affective disorders, particularly major depression. Given the limited evidence relating to the potential role of proinflammatory cytokines in generalised anxiety disorder (GAD), we aimed to examine peripheral proinflammatory cytokines in Chinese patients with GAD. METHODS: A case-controlled cross-sectional study design, with recruitment of 48 patients with first episode GAD and 48 matched healthy controls. All participants completed measures of anxiety using well-established questionnaires, and serum levels of pro-inflammatory cytokines were measured using multiplex technology. RESULTS: Serum levels of CRP, IL-1α, IL-2, IL-6, IL-8, IL-12, IFN-γ, and GM-CSF were significantly higher in the GAD group in comparison to the control group (p < 0.05). Pearson correlation revealed significant positive correlations between anxiety measures and serum levels of CRP, IL-1α, IL-6, IL-8, IFN-γ, and GM-CSF (p < 0.05). LIMITATIONS: The cross-sectional study design does not permit definite conclusions on causal directions between inflammation and GAD. The study was limited to a panel of 8 cytokines and does not exclude the possibility of other important cytokines being involved. CONCLUSIONS: These findings indicate an elevated peripheral proinflammatory response, and provide further support for low grade inflammation in GAD. Further research may identify an 'inflammatory signature' for diagnosis and treatment response, and guide the search for novel pharmacological interventions.

Comparison of Ecological Micro-Expression Recognition in Patients with Depression and Healthy Individuals.

Previous studies have focused on the characteristics of ordinary facial expressions in patients with depression, and have not investigated the processing characteristics of ecological micro-expressions (MEs, i.e., MEs that presented in different background expressions) in these patients. Based on this, adopting the ecological MEs recognition paradigm, this study aimed to comparatively evaluate facial ME recognition in depressed and healthy individuals. The findings of the study are as follows: (1) background expression: the accuracy (ACC) in the neutral background condition tended to be higher than that in the fear background condition, and the reaction time (RT) in the neutral background condition was significantly longer than that in other backgrounds. The type of ME and its interaction with the type of background expression could affect participants' ecological MEs recognition ACC and speed. Depression type: there was no significant difference between the ecological MEs recognition ACC of patients with depression and healthy individuals, but the patients' RT was significantly longer than that of healthy individuals; and (2) patients with depression judged happy MEs that were presented against different backgrounds as neutral and judged neutral MEs that were presented against sad backgrounds as sad. The present study suggested the following: (1) ecological MEs recognition was influenced by background expressions. The ACC of happy MEs was the highest, of neutral ME moderate and of sadness and fear the lowest. The response to the happy MEs was significantly shorter than that of identifying other MEs. It is necessary to conduct research on ecological MEs recognition; (2) the speed of patients with depression in identifying ecological MEs was slower than of healthy individuals; indicating that the patients' cognitive function was impaired; and (3) the patients with depression showed negative bias in the ecological MEs recognition task, reflecting the lack of happy ME recognition ability and the generalized identification of sad MEs in those patients.