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Abstract Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method — multiple genetic abnormality sequencing (MGA-Seq) — to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA’s transcriptional regulatory function.

Extracting polyphenolic bioactive compounds from Pinus elliottii needles, a forestry residue, promises economic and environmental benefits, however, relevant experimental data are lacking. Herein, a comprehensive investigation of the polyphenolic composition of pine needles (PNs) was carried out. Ultrasound-Assisted Extraction (UAE) was applied to extract the polyphenolic compounds of pine needles. The optimal conditions of extracts were determined by Response Surface Methodology (RSM). The maximum total phenolic content (TPC) of 40.37 mg GAE/g PNs was achieved with solid–liquid ratio of 1:20, 60 % ethanol, and 350 W for 25 min at 45 °C. Polyphenolic extracts showed antioxidant activity in scavenging free radicals and reducing power (DPPH, IC50 41.05 μg/mL; FRAP 1.09 mM Fe2+/g PNs; ABTS, IC50 214.07 μg/mL). Furthermore, the second-order kinetic model was also constructed to describe the mechanism of the UAE process, with the extraction activation energy estimated at 12.26 kJ/mol. In addition, 37 compounds in PNs were first identified by UHPLC-Q-Exactive Orbitrap MS/MS, including flavonoids and phenolic acids. The results suggest that Ultrasound-Assisted is an effective method for the extraction of natural polyphenolic compounds from pine needles and this study could serve as a foundation for utilizing phenolics derived from PNs in the food and pharmaceutical industries.

Here the authors delineate the dynamic changes in 3D genome and epigenome of differentiating macrophages and during infection with Mycobacterium tuberculosis. They reveal a role for NF-κB upon infection and identify SNPs in disease-susceptible loci, including rs1873613 that is located in the anchor of a dynamic chromatin loop.

BackgroundThe neutrophil to lymphocyte ratio (NLR) is a cost-effective and easily identifiable inflammatory biomarker that has been shown to be closely associated with tumor prognosis and predict survival in patients with multiple malignancies. However, the predictive value of NLR in patients with gastric cancer (GC) treated with immune checkpoint inhibitors (ICIs) has not been fully explored. Therefore, we conducted a meta-analysis to explore the potential of NLR as a predictor of survival in this population.MethodsWe systematically searched the PubMed, Cochrane Library, and EMBASE databases from inception to the present for observational researches on NLR and its relationship with progression or survival in GC patients receiving ICIs. To assess the prognostic significance of NLR on overall survival (OS) or progression-free survival (PFS), we used fixed or random-effect models to derive and combine hazard ratios (HRs) with 95% confidence intervals (CIs). We also examined the relationship between NLR and treatment efficacy by calculating relative risks (RRs) with 95% CIs for objective response rate (ORR) and disease control rate (DCR) in patients with GC receiving ICIs.ResultsNine studies of 806 patients were eligible. OS and PFS data were obtained from 9 and 5 studies, respectively. In nine studies, NLR was associated with poor survival, the pooled HR was 1.98 (95% CI 1.67- 2.35, p < 0.001), indicating a significant association between high NLR and worse OS. We conducted subgroup analyses based on study characteristics to confirm the robustness of our findings. A relationship between NLR and PFS were reported in five studies with a HR of 1.49 (95% CI 0.99- 2.23, p = 0.056), which was not significantly associated. Pooling four studies that examined the correlation between NLR and ORR/DCR in GC patients, we observed a significant correlation between NLR and ORR (RR = 0.51, p = 0.003), but no significant correlation between NLR and DCR (RR = 0.48, p = 0.111).ConclusionIn summary, this meta-analysis indicates that increased NLR is significantly linked to worse OS in patients with GC receiving ICIs. In addition, lowering NLR can improve ORR. Thus, NLR can serve as a predictor for prognosis and treatment response in GC patients treated with ICIs. Nevertheless, further high-quality prospective studies are required to verify our findings in the future.

Abstract Background Stromal interaction molecule (STIM) 2 is a key calcium-sensing molecule that regulates the stabilization of calcium ions (Ca2+) and therefore regulates downstream Ca2+-associated signaling and cellular events. We hypothesized that STIM2 regulates epithelial-mesenchymal transition (EMT) to promote breast cancer metastasis. Methods We determined the effects of gain, loss, and rescue of STIM2 on cellular motility, levels of EMT-related proteins, and secretion of transforming growth factor-β (TGF-β). We also conducted bioinformatics analyses and in vivo assessments of breast cancer growth and metastasis using xenograft models. Results We found a significant association between STIM2 overexpression and metastatic breast cancer. STIM2 overexpression activated the nuclear factor of activated T cells 1 (NFAT1) and TGF-β signaling. Knockdown of STIM2 inhibited the motility of breast cancer cells by inhibiting EMT via specific suppression of NFAT1 and inhibited mammary tumor metastasis in mice. In contrast, STIM2 overexpression promoted metastasis. These findings were validated in human tissue arrays of 340 breast cancer samples for STIM2. Conclusion Taken together, our results demonstrated that STIM2 specifically regulates NFAT1, which in turn regulates the expression and secretion of TGF-β1 to promote EMT in vitro and in vivo, leading to metastasis of breast cancer.

Background: This study provides a national profile of major work safety accidents in China, which cause more than 10 fatalities per accident, intended to provide scientific basis for prevention measures and strategies to reduce major work safety accidents and deaths. Methods: Data from 2003-2012 Census of major work safety accidents were collected from State Administration of Work Safety System (SAWS). Published literature and statistical yearbook were also included to implement information. We analyzed the frequency of accidents and deaths, trend, geographic distribution and injury types. Additionally, we discussed the severity and urgency of emergency rescue by types of accidents. Results: A total of 877 major work safety accidents were reported, resulting in 16,795 deaths and 9,183 injuries. The numbers of accidents and deaths, mortality rate and incidence of major accidents have declined in recent years. The mortality rate and incidence was 0.71 and 1.20 per 106 populations in 2012, respectively. Transportation and mining contributed to the highest number of major accidents and deaths. Major aviation and railway accidents caused more casualties per incident, while collapse, machinery, electrical shock accidents and tailing dam accidents were the most severe situation that resulted in bigger proportion of death. Conclusion: Ten years’ major work safety accident data indicate that the frequency of accidents and number of deaths was declined and several safety concerns persist in some segments.

People living with HIV or AIDS (PLWHA) experienced severe medical discrimination which is seriously affecting their lives. However, few studies examined the epidemic characteristics of self-perceived medical discrimination from the discrimination objects such as PLWHA. Therefore, we aimed to investigate the epidemiological status and analyze the influential factors of the self-perceived medical discrimination on PLWHA in South China. The self-designed questionnaire was used to investigate the medical discrimination status of the 443 infected persons, who were randomly recruited from the representative AIDS designated hospitals in Guangdong Province in South China. The results showed that 49.0% of PLWHA experienced medical discrimination, and 55.3% received discriminatory treatment, 48.4% experienced refusal of treatment, 36.4% had private information leaked and 12.9% received mandatory test. However, 52.2% patients chose to endure discrimination in silence. Compared with the Asymptomatic HIV-infected patients, AIDS patients perceived more medical discrimination. The Logistic regression analysis indicated that PLWHA self-perceived medical discrimination status was influenced by 4 factors: the voluntary of first medical detection, the route of transmission, the stage of the disease and the familiarity with the HIV/AIDS-related law. Additionally, the two dimensions of the life quality scale were influenced by medical discrimination, namely, overall function and disclosure worry. Ultimately, our study provides a better understanding of the relationship between infection status, quality of life and the medical discrimination they experienced or perceived. It will help health professionals and policy makers to develop tailored behavioral and policy-oriented intervention strategies for PLWHA to tackle different types of medical discrimination in high-risk settings. [ABSTRACT FROM AUTHOR]

Immunocytes dynamically reprogram their gene expression profiles during differentiation and immunoresponse. However, the underlying mechanism remains elusive. Here, we develop a single-cell Hi-C method and systematically delineate the 3D genome and dynamic epigenetic atlas of macrophages during these processes. We propose "degree of disorder" to measure genome organizational patterns inside topologically-associated domains, which is correlated with the chromatin epigenetic states, gene expression, and chromatin structure variability in individual cells. Furthermore, we identify that NF-κB initiates systematic chromatin conformation reorganization upon Mycobacterium tuberculosis infection. The integrated Hi-C, eQTL, and GWAS analysis depicts the atlas of the long-range target genes of mycobacterial disease susceptible loci. Among these, the SNP rs1873613 is located in the anchor of a dynamic chromatin loop with LRRK2, whose inhibitor AdoCbl could be an anti-tuberculosis drug candidate. Our study provides comprehensive resources for the 3D genome structure of immunocytes and sheds insights into the order of genome organization and the coordinated gene transcription during immunoresponse. Here the authors delineate the dynamic changes in 3D genome and epigenome of differentiating macrophages and during infection with Mycobacterium tuberculosis. They reveal a role for NF-κB upon infection and identify SNPs in disease-susceptible loci, including rs1873613 that is located in the anchor of a dynamic chromatin loop. [ABSTRACT FROM AUTHOR]

Background: Symptom phrase recognition is essential to improve the use of unstructured medical consultation corpora for the development of automated question answering systems. A majority of previous works typically require enough manually annotated training data or as complete a symptom dictionary as possible. However, when applied to real scenarios, they will face a dilemma due to the scarcity of the annotated textual resources and the diversity of the spoken language expressions.Methods: In this paper, we propose a composition-driven method to recognize the symptom phrases from Chinese medical consultation corpora without any annotations. The basic idea is to directly learn models that capture the composition, i.e., the arrangement of the symptom components (semantic units of words). We introduce an automatic annotation strategy for the standard symptom phrases which are collected from multiple data sources. In particular, we combine the position information and the interaction scores between symptom components to characterize the symptom phrases. Equipped with such models, we are allowed to robustly extract symptom phrases that are not seen before.Results: Without any manual annotations, our method achieves strong positive results on symptom phrase recognition tasks. Experiments also show that our method enjoys great potential with access to plenty of corpora.Conclusions: Compositionality offers a feasible solution for extracting information from unstructured free text with scarce labels. [ABSTRACT FROM AUTHOR]

The impressive functions of the brain rely on an extensive connectivity matrix between specific neurons, the architecture of which is frequently characterized by one brain nucleus/region connecting to multiple targets, either via collaterals of the same projection neuron or several, differentially specified neurons. Delineating the fine architecture of projection neuron subsets in a specific brain region could greatly facilitate its circuit, computational, and functional resolution. Here, we developed multiple fluorescent rabies viruses (RV) to delineate the fine organization of corticothalamic projection neuron subsets in the primary visual cortex (V1). By simultaneously retrograde labeling multiple distinct subsets of corticothalamic projection neurons in V1 from their target nuclei in thalamus (dLGN, LP, LD), we observed that V1-dLGN corticothalamic projection neurons were densely concentrated in layer VI, except for several sparsely scattered neurons in layer V, while V1-LP and V1-LD corticothalamic projection neurons were localized to both layers V and VI. Meanwhile, we observed a fraction of V1 corticothalamic projection neurons targeting two thalamic nuclei, which was further confirmed by fMOST whole-brain imaging. The multiple fluorescent RV tracing tools can be extensively applied to resolve the architecture of projection neuron subsets in certain brain regions, with a strong potential to delineate the computational and functional organization of these brain regions. [ABSTRACT FROM AUTHOR]

Knowledge graph embedding techniques can be roughly divided into two mainstream, translational distance models and semantic matching models. Though intuitive, translational distance models fail to deal with the circle structure and hierarchical structure in knowledge graphs. In this paper, we propose a general learning framework named TransX-pa, which takes various models (TransE, TransR, TransH and TransD) into consideration. From this unified viewpoint, we analyse the learning bottlenecks are: (i) the common assumption that the inverse of a relation r is modelled as its opposite − r; and (ii) the failure to capture the rich interactions between entities and relations. Correspondingly, we introduce position-aware embeddings and self-attention blocks, and show that they can be adapted to various translational distance models. Experiments are conducted on different datasets extracted from real-world knowledge graphs Freebase and WordNet in the tasks of both triplet classification and link prediction. The results show that our approach makes a great improvement, showing a better, or comparable, performance with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Automatic question answering (QA) system is the inevitable trend of future search engines. As the essential steps of QA, question classification and text retrieval both require algorithms to capture the semantic information and syntactic structure of natural language. This paper proposes dependency-based convolutional networks to learn a representation of sentences. First, we use dependency layer to map discrete word depth on the dependency tree of a sentence into continuous real space. Then, the mapping result serves as weight of word vectors and convolutional kernels are employed as feature extractors for further specific tasks. The method proposed allows convolutional networks to take the advantage of higher representational ability of dependency structure. Experiments involving three tasks including text classification, duplicate classification and text pairs ranking confirm the advantages of our model. [ABSTRACT FROM AUTHOR]

Recognizing standard medical concepts in the colloquial text is significant for kinds of applications such as the medical question answering system. Recently, word-level neural network methods, which can learn complex informal expression features, achieved remarkable performance on this task. However, they have two main limitations: (1) Existing word-level methods cannot learn character structure features inside words and suffer from "Out-of-vocabulary" (OOV) words, which are common in noisy colloquial text. (2) Since these methods handle the normalization task as a classification issue, concept phrases are represented by category labels. Hence the word morphological information inside the concept is lost. In this work, we present a multi-task character-level attentional network model for medical concept normalization. Specifically, the character-level encoding scheme of our model can alleviate the OOV word problem. The attention mechanism can effectively exploit the word morphological information through multi-task training. It generates higher attention weights on domain-related positions in the text sequence, helping the downstream convolution focus on the characters that are related to medical concepts. To test our model, we first introduce a labeled Chinese dataset (overall 314,991 records) for this task. Other two real-world English datasets are also used. Our model outperforms state-of-the-art methods on all three datasets. Besides, by adding four types noises to the datasets, we validate the robustness of our model against common noises in the colloquial text. [ABSTRACT FROM AUTHOR]

Phenytoin ( PHT) is a commonly prescribed first-line antiepileptic drug. However, long-term administration of PHT can cause memory loss and balance disturbance. Gastrodin ( GD) is the major bioactive component in Tianma and has sedative, anticonvulsive, memory strengthening, and neuroprotective effects. To combine the two drugs seems attractive; however, little was known about the efficacy of combination therapy. In this study, convulsive attack was successfully induced by penicillin. Isobolographic analysis, memory and balance behavior test, histopathological examination, and Western blot analysis were used to investigate whether the combination therapy of GD and PHT can enhance anticonvulsive effect and reduce the side effects associated with PHT. The GD alone (950.60 mg/kg) and the PHT alone (45.50 mg/kg) could produce an anticonvulsive effect, while comparable effect could be produced by PHT : GD = 1 : 50 (8.59 : 429.27 mg/kg), which reduce the dose of PHT by 81% and GD by 55%. After the chronic anticonvulsive experiments of 16 days, the balance disturbance and short-/long-term memory loss were observed in the PHT group, while the PHT + GD therapy can protect the normal balance and memory function. The neuron morphology of hippocampus was preserved, and the number of surviving neurons after combination therapy was more than the model group. The amount of NF-κB (p65) expression was increased in combination group. All above suggested the potential of the combination of PHT and GD enhances the anticonvulsive effect and the neuroprotective effect and reduces the PHT-associated memory and balance disturbance. The PHT + GD strategy would provide new possibilities as a novel promising methodology to treat epileptic patients. [ABSTRACT FROM AUTHOR]

Background: Stromal interaction molecule (STIM) 2 is a key calcium-sensing molecule that regulates the stabilization of calcium ions (Ca2+) and therefore regulates downstream Ca2+-associated signaling and cellular events. We hypothesized that STIM2 regulates epithelial-mesenchymal transition (EMT) to promote breast cancer metastasis.Methods: We determined the effects of gain, loss, and rescue of STIM2 on cellular motility, levels of EMT-related proteins, and secretion of transforming growth factor-β (TGF-β). We also conducted bioinformatics analyses and in vivo assessments of breast cancer growth and metastasis using xenograft models.Results: We found a significant association between STIM2 overexpression and metastatic breast cancer. STIM2 overexpression activated the nuclear factor of activated T cells 1 (NFAT1) and TGF-β signaling. Knockdown of STIM2 inhibited the motility of breast cancer cells by inhibiting EMT via specific suppression of NFAT1 and inhibited mammary tumor metastasis in mice. In contrast, STIM2 overexpression promoted metastasis. These findings were validated in human tissue arrays of 340 breast cancer samples for STIM2.Conclusion: Taken together, our results demonstrated that STIM2 specifically regulates NFAT1, which in turn regulates the expression and secretion of TGF-β1 to promote EMT in vitro and in vivo, leading to metastasis of breast cancer. [ABSTRACT FROM AUTHOR]