bluuebunny/crossref_metadata_2025 huggingface dataset:
The multifaceted roles of ER and Golgi in metabolic cardiomyopathy
Authors: Raja Rida , Fonseka Oveena , Ganenthiran Haresh , Andrea-Ruiz-Velasco  , Liu Wei
Published: September 2022

Metabolic cardiomyopathy is a significant global financial and health challenge; however, pathophysiological mechanisms governing this entity remain poorly understood. Among the main features of metabolic cardiomyopathy, the changes to cellular lipid metabolism have been studied and targeted for the discovery of novel treatment strategies obtaining contrasting results. The endoplasmic reticulum (ER) and Golgi apparatus (GA) carry out protein modification, sorting, and secretion activities that are more commonly studied from the perspective of protein quality control; however, they also drive the maintenance of lipid homeostasis. In response to metabolic stress, ER and GA regulate the expression of genes involved in cardiac lipid biogenesis and participate in lipid droplet formation and degradation. Due to the varied roles these organelles play, this review will focus on recapitulating the alterations and crosstalk between ER, GA, and lipid metabolism in cardiac metabolic syndrome.
Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment
Authors: Frank Ellen , Wallace Meredith L. , Matthews Mark J. , Kendrick Jeremy , Leach Jeremy , Moore Tara , Aranovich Gabriel , Choudhury Tanzeem , Shah Nirav R. , Framroze Zeenia , Posey Greg , Burgess Samuel A. , Kupfer David J.
Published: September 2022

We conducted a 16-week randomized controlled trial in psychiatric outpatients with a lifetime diagnosis of a mood and/or anxiety disorder to measure the impact of a first-of-its-kind precision digital intervention software solution based on social rhythm regulation principles. The full intent-to-treat (ITT) sample consisted of 133 individuals, aged 18–65. An exploratory sub-sample of interest was those individuals who presented with moderately severe to severe depression at study entry (baseline PHQ-8 score ≥15; N = 28). Cue is a novel digital intervention platform that capitalizes on the smartphone's ability to continuously monitor depression-relevant behavior patterns and use each patient's behavioral data to provide timely, personalized “micro-interventions,” making this the first example of a precision digital intervention of which we are aware. Participants were randomly allocated to receive Cue plus care-as-usual or digital monitoring only plus care as usual. Within the full study and depressed-at-entry samples, we fit a mixed effects model to test for group differences in the slope of depressive symptoms over 16 weeks. To account for the non-linear trajectory with more flexibility, we also fit a mixed effects model considering week as a categorical variable and used the resulting estimates to test the group difference in PHQ change from baseline to 16 weeks. In the full sample, the group difference in the slope of PHQ-8 was negligible (Cohen's d = −0.10); however, the Cue group demonstrated significantly greater improvement from baseline to 16 weeks (p = 0.040). In the depressed-at-entry sample, we found evidence for benefit of Cue. The group difference in the slope of PHQ-8 (Cohen's d = −0.72) indicated a meaningfully more rapid rate of improvement in the intervention group than in the control group. The Cue group also demonstrated significantly greater improvement in PHQ-8 from baseline to 16 weeks (p = 0.009). We are encouraged by the size of the intervention effect in those who were acutely ill at baseline, and by the finding that across all participants, 80% of whom were receiving pharmacotherapy, we observed significant benefit of Cue at 16 weeks of treatment. These findings suggest that a social rhythm-focused digital intervention platform may represent a useful and accessible adjunct to antidepressant treatment (https://clinicaltrials.gov/ct2/show/NCT03152864?term=ellen+frank&draw=2&rank=3).
Can research help to deliver the promises of inclusive education? The case of students with disabilities in the education marketplace
Authors: Waitoller Federico R. , Beasley Letrice , West TaMia , Randle Stacy
Published: September 2022

In this paper, we engage with the question that frames this special issue: Can research help to deliver the promises of inclusive education? We argue that the answer is not so much a resounding and unquestionable “Yes!” but more of a “yes but…” it depends on what we consider and privilege as research evidence. Using the case of market-driven reforms and their impact on inclusive education for students with disabilities, we question the overemphasis on quantitative research as unbiased rationale for distributing economic and human resources, closing schools, and expanding private/public partnerships to deliver public education. We recommend that policy decision-making account for the history and geography of school districts and the intersectional forms of exclusion experienced by students and families, particularly those who experience interacting forms of oppression at the intersections of disability, race, and class.
Thyroid diseases are associated with coronavirus disease 2019 infection
Authors: Tian Yutian , Zhao Junyu , Wang Tingting , Wang Haipeng , Yao Jinming , Wang Song , Mou Yaru
Published: September 2022

Background

In 2019, there was a global outbreak of new coronary pneumonia. Studies have found that the severity of patients with new coronary pneumonia may be related to their comorbidities. This article discusses the impact of thyroid disease on the severity of new coronary pneumonia through a meta-analysis and provides new treatment ideas for the later treatment and recovery of new coronary pneumonia.

Methods

Databases including PubMed, Embase, Cochrane Library, SINOMED, China national knowledge infrastructure (CNKI), and Wanfang for coronavirus disease 2019 (COVID-19) infection and thyroid diseases were searched. Reference lists of all eligible articles and related previous review articles were handsearched. Fifty-three articles were included to conduct the meta-analysis.

Results

Fifty-three articles with 12,022 COVID-19 infection patients were included in this meta-analysis. The proportion of patients with thyroid diseases in all COVID-19 infection patients fluctuates between 0% and 88.46%. Of the 53 included studies, 22 studies reported the severity of COVID-19 infection and grouped. The fixed-effects model was used to merge odds ratio (OR) values, and the pooled effect size in favor of non-severe patients is 2.62 (95% CI = 1.96–3.49, P < 0.0001), which means that patients with severe COVID-19 infection are more likely to have thyroid diseases. The analysis subgrouped into Asia and Europe shows that patients with COVID-19 severe infection in Asia are 3.77 times more likely to have thyroid diseases than non-severe patients (fixed-effects model: OR = 3.77, 95% CI = 2.66–5.35, P < 0.00001). No significant statistical heterogeneity was found by the heterogeneity analysis (chi-square = 19.85, P = 0.34, I2 = 9%). Severe COVID-19 infection patients are more likely to be complicated by hypothyroidism and low T3 syndrome. The pooled ORs with fixed-effects model are 3.72 (95% CI = 1.62–8.58, P = 0.002) and 5.86 (95% CI = 2.79–12.33, P < 0.00001), respectively.

Conclusion

COVID-19 infection patients with thyroid diseases are very common, and severe patients are more likely to have thyroid diseases. Asian COVID-19 infection, hypothyroidism patients, and patients with low T3 syndrome are more likely to progress to severe condition.

Systematic Review Registration

https://inplasy.com, identifier INPLASY202190079.
The efficacy and safety of luteal phase support with progesterone following ovarian stimulation and intrauterine insemination: A systematic review and meta-analysis
Authors: Casarramona G. , Lalmahomed T. , Lemmen CHC. , Eijkemans MJC. , Broekmans FJM. , Cantineau AEP. , Drechsel KCE.
Published: September 2022

The aim of this systematic review and meta-analysis was to update the current evidence for the efficacy and safety of progesterone luteal phase support (LPS) following ovarian stimulation and intrauterine insemination treatment (OS-IUI) for unexplained or mild male infertility. Four additional studies were identified compared to the previous review in 2017. Twelve RCTs (2631 patients, 3262 cycles) met full inclusion criteria. Results from quantitative synthesis suggest that progesterone LPS after OS-IUI leads to higher live birth (RR 1.38, 95%CI [1.09, 1.74]; 7 RCTs, n=1748) and clinical pregnancy rates (RR 1.38, 95% CI [1.21, 1.59]; 11 RCTs, n=2163) than no LPS or placebo. This effect is specifically present in protocols using gonadotropins for OS-IUI (RR 1.41, 95%CI [1.17, 1.71]; 7 RCTs, n=1114), and unclear in protocols involving clomiphene citrate (RR 1.01, 95% CI [0.05, 18.94]; 2 RCTs, n=138). We found no effect of progesterone LPS on multiple pregnancy or miscarriage rates. No correlation between drug-dosage or duration of treatment and effect size was seen. Though our results suggest both benefit and safety of progesterone LPS in OS-IUI, evidence is of low to moderate quality and additional well-powered trials are still mandatory to confirm our findings and justify implementation in daily practice.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=292325, identifier CRD42021292325.
Hydrogen saline water accelerates fracture healing by suppressing autophagy in ovariectomized rats
Authors: Guo Jialiang , Tian Siyu , Wang Zhongzheng , Wang Yuchuan , Zhang Xiaojuan , Zhang Yingze , Hou Zhiyong , Dong Weichong
Published: September 2022

Objective

The treatment of osteoporotic fractures is difficult, and to minimize the negative result or poor functional rehabilitation, this study focuses on hydrogen water (HRW) to test its effect on the process of menopausal osteoporotic fracture healing and its relationship with autophagy and to try to reveal the potential mechanism of action of HRW on osteoporotic fractures.

Materials and methods

A rat osteoporotic fracture model was established, and HRW was systematically applied with or without 3MA. The results were analyzed with X-rays, micro-CT scans, serum biomarker analysis, biomechanical tests, histopathology, immunohistochemistry, and Western blotting. The sham, OVX, OH (OVX+HRW) and OHA (OVX+HRW+3MA) groups were formed and compared.

Results

Increased oxidative stress and autophagy levels were necessary physiological responses in the process of fracture healing. It was found that systemic HRW treatment slightly suppressed autophagy and then activated the Keap1-Nrf2 signaling pathway by maintaining the Keap1-Nrf2-P62 interaction and improved the osteoporotic fracture healing process.

Conclusion

HRW treatment activated the Keap1-Nrf2 signaling pathway to antagonize cellular stress by suppressing autophagy levels, especially at the early stage of the fracture healing process, and this was beneficial to osteoporotic fracture healing in rats.
Potential biomarkers for clinical outcomes of IVF cycles in women with/without PCOS: Searching with metabolomics
Authors: Guan Shang-yue , Liu Yuan-yuan , Guo Yuhan , Shen Xiao-xue , Liu Yan , Jin Hai-xia
Published: September 2022

Background

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrinological and metabolic disorder which is the common cause of female infertility. The dysmetabolism displayed in it has not been completely ascertained. Metabonomics may shed light on understanding many small molecule endogenous metabolites and their associated metabolic pathways.

Objective

To analyze the different metabolites and related metabolic pathways in follicular fluid and embryo culture fluid of PCOS and non-PCOS groups. Finding markers predictable for clinical outcomes of in vitro fertilization-embryo transfer (IVF-ET) treatment.

Population and sample

60 women who underwent IVF-ET were selected, including 30 with PCOS and 30 with the fallopian tubal issues only. We collected the first tube follicular fluid (FF) of all patients at the time of oocyte pick up and the waste embryo culture medium (ECM) after D3 high-quality embryo transplant.

Methods

All samples were performed nontargeted Ultra High Performance Liquid Chromatography-Mass Spectrometry (UHPLC-QE-MS) analysis. Related metabolic pathways were screened by KEGG annotation. To search potential indicators, the logistic regression was made combined with clinical data.

Mean outcome measures

Predictive performance of markers of clinical outcomes (pregnancy rate, delivery rate, live birth rate, miscarriage rate) of assisted reproductive technology (ART).

Results

Comparing the PCOS group against the non-PCOS group, we found 11 significantly different metabolites in the FF and 56 in the ECM. There are a total of 11 kinds of biomarkers associated with clinical outcomes. Androsterone sulfate, Glycerophosphocholine, and Elaidic carnitine seem robust to predict the abortion rate of the PCOS group, with an AUC of 0.941, 0.933, 0.933, respectively. The glycerol phospholipid metabolic pathway is enriched in both the follicular fluid and embryo culture fluid.

Conclusions

The differential metabolites were mainly a variety of lipids. Some of them can predict clinical outcomes to a certain extent.
Collaborative optimization of train timetable and speed trajectory considering stochastic photovoltaic power: A two-step approach
Authors: Li Jinpeng , Feng Minling , Wu Chaoxian , Lu Shaofeng
Published: September 2022

Faced with the integrated system composed of the train power system, the photovoltaic (PV) power system, and the energy storage system (ESS), this research studies the energy-efficient operation and energy management strategy from the perspective of both train optimal control and timetable optimization, aiming at achieving a long-term energy consumption reduction. A two-step approach for collaboratively optimizing the train timetable, speed trajectory, and energy management strategy considering the stochastic characteristics of PV power generation is proposed to solve this large-scale complex problem. Before the two-step approach, a mixed-integer linear programming (MILP) model is established to optimize the energy consumption of the inter-station operation. On this basis, explicit energy consumption expressions for all inter-stations of the entire line are obtained by the proposed data fitting method. The historical PV power data is clustered to generate scenarios with different probabilities to characterize the stochastic PV power. The first step of this two-step approach is to minimize the total energy consumption expectations of all inter-stations determined by the obtained explicit energy consumption expressions to optimize the timetable while ensuring the total time and time window constraints are met. The second step is to minimize the weighted sum of energy consumption under all possible scenarios to obtain the optimal speed trajectory and energy management strategy based on the optimized timetable obtained in the first step. The validity of the model is verified by case studies using the real data of Qingdao Metro Line 11 under both scenarios with and without PV power. This study provides a novel method for energy-efficient operation and energy management of the integrated system and demonstrates the prospect of the proposed two-step stochastic optimization in reducing the net grid-supplied energy for the long-term operation of urban rail transportation systems.
Experimental study for thermal methane cracking reaction to generate very pure hydrogen in small or medium scales by using regenerative reactor
Authors: Yousefi Mahdi , Donne Scott
Published: September 2022

Non-catalytic thermal methane cracking (TMC) is an alternative for hydrogen manufacturing and traditional commercial processes in small-scale hydrogen generation. Supplying the high-level temperatures (850–1800°C) inside the reactors and reactor blockages are two fundamental challenges for developing this technology on an industrial scale (Mahdi Yousefi and Donne, 2021). A regenerative reactor could be a part of a solution to overcome these obstacles. This study conducted an experimental study in a regenerative reactor environment between 850 and 1,170°C to collect the conversion data and investigate the reactor efficiency for TMC processes. The results revealed that the storage medium was a bed for carbon deposition and successfully supplied the reaction’s heat, with more than 99.7% hydrogen yield (at more than 1,150°C). Results also indicated that the reaction rate at the beginning of the reactor is much higher, and the temperature dependence in the early stages of the reaction is considerably higher. However, after reaching a particular concentration of Hydrogen at each temperature, the influence of temperature on the reaction rate decreases and is almost constant. The type of produced carbon in the storage medium and its auto-catalytic effect on the reactions were also investigated. Results showed that carbon black had been mostly formed but in different sizes from 100 to 2000 nm. Increasing the reactor temperature decreased the size of the generated carbon. Pre-produced carbon in the reactor did not affect the production rate and is almost negligible at more than 850°C.
A hybrid SVR with the firefly algorithm enhanced by a logarithmic spiral for electric load forecasting
Authors: Zhang Weiguo , Gu Linlin , Shi Yang , Luo Xiaodong , Zhou Hu
Published: September 2022

Accurate forecasting of an electric load is vital in the effective management of a power system, especially in flourishing regions. A new hybrid model called logarithmic spiral firefly algorithm-support vector regression (LS-FA-SVR) is proposed to promote the performance of electric load forecasting. The new hybrid model is acquired by combining the support vector regression, firefly algorithm, and logarithmic spiral. Half-hourly electric load from five main regions (NSW, QLD, SA, TAS, and VIC) of Australia are used to train and test the proposed model. By comparing the model results with observed data on the basis of the root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percent error (MAPE), the performance of the proposed hybrid model is the most outstanding among all the considered benchmark models. Hence, the results of this study show that the hybrid model LS-FA-SVR is preferable and can be applied successfully because of its high accuracy.
Synchrophasor data-based inertia estimation for regional grids in interconnected power systems
Authors: Zhang Yiping , Qi Feng , He Yangdong , Wang Bo , Yang Deyou
Published: September 2022

The inertia level is a significant indicator that guides operators to integrate renewable power generation into the power system for safe operation. In this study, a method that can estimate the effective inertia of power grids located in different regions in the interconnected system is proposed by using the synchronous measurement data. Based on the equivalent swing equation formed as a second-order oscillator, the inertia is expressed as a ratio of the time-evolution solution of this equation. To avoid a meaningless ratio, the Hilbert transformation is leveraged to recast the inertia analytical expression, which is composed of the time-independent characteristic parameters of the oscillation signal. Furthermore, the signal identification technique is employed to extract the characteristic parameters from the synchronized measurements so that the proposed scheme can estimate the regional inertia by using only the outputs measured by the synchorphasor measurement units. A comparison of the simulation results and methods validate the effectiveness and robustness of the proposed method.
Sorption of benzo(a)pyrene and of a complex mixture of petrogenic polycyclic aromatic hydrocarbons onto polystyrene microplastics
Authors: Martínez-Álvarez Ignacio , Le Menach Karyn , Devier Marie-Hélène , Cajaraville Miren P. , Orbea Amaia , Budzinski Hélène
Published: September 2022

Microplastics (MPs) largely occur in aquatic ecosystems due to degradation of larger plastics or release from MP-containing products. Due to the hydrophobic nature and large specific surface of MPs, other contaminants, such as polycyclic aromatic hydrocarbons (PAHs), can potentially sorb onto MPs. Several studies have addressed the potential impact of MPs as vectors of PAHs for aquatic organisms. Therefore the role of MPs as sorbents of these compounds should be carefully investigated. The present study aimed to determine the sorption capacity of benzo(a)pyrene (B(a)P), as a model pyrolytic PAH, to polystyrene (PS) MPs of different sizes (4.5 and 0.5 μm). In addition, the sorption of PAHs present in the water accommodated fraction (WAF) of a naphthenic North Sea crude oil to 4.5 μm MPs was also studied as a model of a complex mixture of petrogenic PAHs that could appear in oil-polluted environments. The results indicated that 0.5 μm MPs showed higher maximum sorption capacity (Qmax) for B(a)P (145–242.89 μg/g) than 4.5 μm MPs (30.50–67.65 μg/g). From the WAF mixture, naphthalene was sorbed at a higher extent than the other PAHs to 4.5 μm MPs but with weak binding interactions (Kf = 69.25 L/g; 1/n = 0.46) according to the analysis of the aqueous phase, whereas phenanthrene showed stronger binding interactions (Kf = 0.24 L/g; 1/n = 0.98) based on the analysis of the solid phase. Sorption of PAHs of the complex WAF mixture to 4.5 μm MPs was relatively limited and driven by the hydrophobicity and initial concentration of each PAH. Overall, the results indicate that sorption estimations based solely on the analysis of the aqueous phase could overestimate the capacity of MPs to carry PAHs. Therefore, controlled laboratory assays assessing the “Trojan Horse effect” of MPs for aquatic organisms should consider these findings in order to design accurate and relevant experimental procedures.
Residues, dissipation, and dietary risk assessment of oxadixyl and cymoxanil in cucumber
Authors: Fan Jiqiao , Li Li
Published: September 2022

Oxadixyl and cymoxanil are widely used for controlling downy mildew in cucumber; however, there are few systematic studies on monitoring residue levels of these two pesticides in cucumber under greenhouse and open field conditions. In this study, a simplified quick, easy, cheap, effective, rugged, and safe (QuEChERS) method was applied to analyze target compounds in cucumber. The average recoveries of oxadixyl and cymoxanil in cucumber ranged from 96% to 102%, with relative standard deviations (RSDs) of 1.8%–4.0%. The limits of quantification (LOQs) for two pesticides were both 0.01 mg/kg. The dissipation of oxadixyl was in accordance with a first-order kinetics equation, with half-lives ranging from 1.8 to 3.1 days. At the pre-harvest interval (PHI) of 3 or 5 days, the residue levels of oxadixyl in cucumber under open field conditions were higher than those under greenhouse conditions. Compared to oxadixyl, the cymoxanil degraded quickly, and its residues were below LOQ on the 3rd or 5th day after the last application. The terminal residues of oxadixyl and cymoxanil in the cucumber were both lower than the maximum residue limits (MRLs) in China. The risk quotient (RQ) used for dietary risk assessment was 1.8%–3.5% and 0.26%–0.51% for oxadixyl and cymoxanil, respectively. The results showed that the risks of these two pesticides used on cucumber at the experimental dosages are comparably acceptable for Chinese consumers of different gender and age groups. This study provides a reference data to use oxadixyl and cymoxanil scientifically and rationally.
Empirical analysis of the role of new energy transition in promoting china’s economy
Authors: Liu Xiaofei , Li Jingcheng , Han Lina , Zhou Biao
Published: September 2022

In order to accelerate the development of new energy industry and social economy, this paper presents an empirical analysis of the role of new energy transformation in promoting China’s economy. On the basis of analyzing the concept and types of new energy, the necessity of transformation and upgrading of new energy industry is discussed. The new energy consumption data from 2010 to 2020 and China’s GDP data are selected as the basic data, and the MS-VAR model is used as the base model for the empirical analysis. The model combines the Markov zone transition model and the autoregressive model, which is suitable for analyzing non-linear problems. The results of the empirical analysis show that the new energy transition is an important way to promote new energy consumption, and it plays a role in promoting the balanced development of China’s economic growth. Combining the results of the empirical analysis, this paper gives suggestions related to the new energy transition from the institutional, economic and technological perspectives.
Development and application of flood impact maps under climate change scenarios: A case study of the Yilan area of Taiwan
Authors: Hsiao Yi-Hua , Chen Chun-Che , Chao Yi-Chiung , Li Hsih-Chi , Ho Ching-Hsien , Hsu Chih-Tsung , Yeh Keh-Chia
Published: September 2022

Flooding is the main disaster type in Taiwan and is usually caused by typhoons and heavy rainfall. To understand the flood impacts in Taiwan caused by increasing rainfall due to global warming, this study adopts a high-resolution atmospheric model (HiRAM) under the representative concentration pathway (RCP) 8.5 scenario to project future changes in flood impact. For the flood simulation, the SOBEK flood model was used to determine the maximum accumulated flooding depth and flood probability in the two periods of the present and the middle of the 21st century. Yilan County, one of the most flood-prone areas in Taiwan, was chosen as a demonstration case for the development of flood impact maps. According to the results of flood map application, flooded areas were predicted to increase in the middle period of the 21st century due to increasing rainfall, especially in paddy fields, maricultural farms, and stock farms. From the base period to the middle of the 21st century, the area of flooding impacts was projected to increase from 24% to 40% in paddy fields, from 9% to 15% in maricultural farms, and from less than 1% to 9% in stock farms. These results show that the development of flood maps can help elucidate the actual impacts of climate change in Taiwan and serve as a scientific basis for adaptation actions.
Genome-wide comparison and in silico analysis of splicing factor SYF2/NTC31/p29 in eukaryotes: Special focus on vertebrates
Authors: Huang Bao-Xing , Jia Zi-Chang , Yang Xue , Cheng Chao-Lin , Liu Xiao-Rong , Zhang Jianhua , Chen Mo-Xian , Yang Jing-Fang , Chen Yun-Sheng
Published: September 2022

The gene SYF2—an RNA splicing factor—can interact with Cyclin D-type binding protein 1 (GICP) in many biological processes, including splicing regulation, cell cycle regulation, and DNA damage repair. In our previous study we performed genome-wide identification and functional analysis of SYF2 in plant species. The phylogenetic relationships and expression profiles of SYF2 have not been systematically studied in animals, however. To this end, the gene structure, genes, and protein conserved motifs of 102 SYF2 homologous genes from 91 different animal species were systematically analyzed, along with conserved splicing sites in 45 representative vertebrate species. A differential comparative analysis of expression patterns in humans and mice was made. Molecular bioinformatics analysis of SYF2 showed the gene was conserved and functional in different animal species. In addition, expression pattern analysis found that SYF2 was highly expressed in hematopoietic stem cells, T cells, and lymphoid progenitor cells; in ovary, lung, and spleen; and in other cells and organs. This suggests that changes in SYF2 expression may be associated with disease development in these cells, tissues, or organs. In conclusion, our study analyzes the SYF2 disease resistance genes of different animal species through bioinformatics, reveals the relationship between the SYF2 genotype and the occurrence of certain diseases, and provides a theoretical basis for follow-up study of the relationship between the SYF2 gene and animal diseases.
Integrative analysis of synovial sarcoma transcriptome reveals different types of transcriptomic changes
Authors: Sun Zhengwang , Yin Mengchen , Ding Yi , Zhu Zixu , Sun Yangbai , Li Kun , Yan Wangjun
Published: September 2022

Background: Synovial sarcoma (SS) is a rare and aggressive cancer that can come from distinct soft tissue types including muscle and ligaments. However, the transcriptomic landscape of SS is still poorly understood. This study aimed to systematically dissect the changes in SS transcriptome from different perspectives.

Methods: We performed deep total RNA sequencing on ten paired Synovial sarcoma and tumor-adjacent tissues to systematically dissect the transcriptomic profile of SS in terms of gene expression, alternative splicing, gene fusion, and circular RNAs.

Results: A total of 2,309 upregulated and 1,977 downregulated genes were identified between SS and tumor-adjacent tissues. Those upregulated genes could lead to the upregulation of the cell cycle, ribosome, and DNA replication pathways, while the downregulated genes may result in the downregulation of a set of metabolic biological processes and signaling pathways. Moreover, 2,511 genes (including 21 splicing factors) were differentially alternative spliced, indicating that the deregulation of alternative splicing could be one important factor that contributes to tumorigenesis. Additionally, we identified the known gene fusions of SS18-SSX1/SSX2 as well as 11 potentially novel gene fusions. Interestingly, 49 circular RNAs were differentially expressed and their parental genes could function in muscle contraction and muscle system processes.

Conclusions: Collectively, our comprehensive dissection of the transcriptomic changes of SS from both transcriptional and post-transcriptional levels provides novel insights into the biology and underlying molecular mechanism of SS.
Interpreting the spectrum of gamma-secretase complex missense variation in the context of hidradenitis suppurativa—An in-silico study
Authors: Mintoff Dillon , Pace Nikolai P. , Borg Isabella
Published: September 2022

Hidradenitis suppurativa (HS) is a disease of the pilosebaceous unit characterized by recurrent nodules, abscesses and draining tunnels with a predilection to intertriginous skin. The pathophysiology of HS is complex. However, it is known that inflammation and hyperkeratinization at the hair follicle play crucial roles in disease manifestation. Genetic and environmental factors are considered the main drivers of these two pathophysiological processes. Despite a considerable proportion of patients having a positive family history of disease, only a minority of patients suffering from HS have been found to harbor monogenic variants which segregate to affected kindreds. Most of these variants are in the ɣ secretase complex (GSC) protein-coding genes. In this manuscript, we set out to characterize the burden of missense pathogenic variants in healthy reference population using large scale genomic dataset thereby providing a standard for comparing genomic variation in GSC protein-coding genes in the HS patient cohort.
Evaluating the effect of tanning response to sun exposure on the risk of skin diseases through Mendelian randomization
Authors: Ping Weidong , Zhao Qiming , Ge Shuhong , Wang Xin , Li Fei , Huang Xiaoxiang
Published: September 2022

Background: Until now, the relevance of the tanning response to sun exposure and skin diseases has incomplete and inconsistent epidemiological observations. In this case, it is valuable to find out the causality of tanning response to sun exposure and skin diseases, and take a step further toward developing effective therapies as well as prevention methods.

Methods: We investigated the causal effect of tanning response to sun exposure on 10 major skin diseases that have been studied in recent large-scale genome-wide association studies (GWASs). Significant independent genetic variants from large-scale GWAS on ease of skin tanning (N = 453,065) are selected as the effective instrumental variables (IVs). For each skin disease, we extracted the summary statistics of those IVs (or their proxies) from the corresponding skin disease-GWAS as the valid IVs. Mendelian randomization (MR) was further performed to evaluate the causal association of ease of skin tanning with each of the skin diseases using different statistical methods, including inverse-variance weighted (IVW), the weighted median, and MR-Egger. Sensitivity analysis was also conducted to evaluate the effect of horizontal pleiotropy and heterogeneity.

Results: We observe significant associations between six skin diseases with tanning response to sun exposure with adjusted p-value derived by IVW less than 0.05 and with nominal p value less than 0.05 at the same time derived by either MR-Egger or weighted median. The six skin diseases include actinic keratosis (IVW FDR = 1.71E-40, MR Egger p-value = 3.46E-22), seborrhoeic keratosis (IVW FDR = 2.97E-4, MR Egger p-value = 1.06E-3), blepharochalasis (IVW FDR = 1.30E-3, MR Egger p-value = 2.91E-4), seborrhoeic dermatitis (IVW FDR = 1.29E-2, MR Egger p-value = 1.23E-2), malignant melanoma of skin (IVW FDR = 2.95E-2, MR Egger p-value = 1.91E-2), and freckles (IVW FDR = 2.95E-2, weighted median p-value = 1.02E-3). Interestingly, we find increased trends of developing all of the six skin diseases with increased tanning response to sun exposure (beta values are positive using IVW, MR-egger, and weighted median methods). We also replicate the association on three skin diseases using an independent outcome GWAS cohort, including malignant melanoma of the skin (replication IVW p-value = 2.13E-39), actinic keratosis (replication IVW p-value = 4.64E-32), and seborrhoeic keratosis (replication IVW p-value = 1.79E-3).

Conclusion: Our observation shows that the tanning response to sun exposure is positively correlated with the development of skin diseases in people of European descent by Mendelian randomization studies. But randomized controlled trials are still needed to add proof to our observations.
Family-based exome sequencing identifies candidate genes related to keratoconus in Chinese families
Authors: Xu Liyan , Yang Kaili , Yin Shanshan , Gu Yuwei , Fan Qi , Wang Yawen , Zhao Dongqing , Ren Shengwei
Published: September 2022

Background: Keratoconus (KC) is a complex corneal disorder with a strong genetic component. The present study aimed to identify candidate genes related to KC in Chinese families.

Methods: Family-based exome sequencing was performed in ten patients suffering from KC who belong to five families with two affected members in each. The candidate rare variants were identified with multi-step bioinformatics analysis. The STRING website was used to perform the protein interaction of the identified genes.

Results: Our analyses identified 32 candidate rare variants in 13 genes by family-based exome sequencing. The molecular analyses of identified genes showed that EPCAM directly interacted with CTNNB1 of the Hippo signaling pathway and focal adhesion pathway, and directly interacted with CTNNB1, CDH1 of the WNT signaling pathway. SHROOM3 directly interacted with ROCK2, ROCK1 of the focal adhesion pathway. SYNE1 directly interacted with MUSK of the extracellular matrix organization pathway. TEK directly interacted with VEGFA, SHC1, PIK3R1, GRB2 of the focal adhesion pathway. TTN directly interacted with CAPN3 of the extracellular matrix organization pathway.

Conclusion: The EPCAM, SHROOM3, SYNE1, TEK, and TTN genes were potential high-risk candidate pathogenic genes of familial KC. The findings might significantly improve our understanding of the genetic etiology of the disease, providing novel insights on KC pathogenesis.
Identification of genomic instability related lncRNA signature with prognostic value and its role in cancer immunotherapy in pancreatic cancer
Authors: Zhu Xiaole , Yu Rong , Peng Yunpeng , Miao Yi , Jiang Kuirong , Li Qiang
Published: September 2022

Background: Increasing evidence suggested the critical roles of lncRNAs in the maintenance of genomic stability. However, the identification of genomic instability-related lncRNA signature (GILncSig) and its role in pancreatic cancer (PC) remains largely unexplored.

Methods: In the present study, a systematic analysis of lncRNA expression profiles and somatic mutation profiles was performed in PC patients from The Cancer Genome Atlas (TCGA). We then develop a risk score model to describe the characteristics of the model and verify its prediction accuracy. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the correlation between tumor immune microenvironment, immune infiltration, immune checkpoint blockade (ICB) therapy, and GILncSig in PC.

Results: We identified 206 GILnc, of which five were screened to develop a prognostic GInLncSig model. Multivariate Cox regression analysis and stratified analysis revealed that the prognostic value of the GILncSig was independent of other clinical variables. Receiver operating characteristic (ROC) analysis suggested that GILncSig is better than the existing lncRNA-related signatures in predicting survival. Additionally, the prognostic performance of the GILncSig was also found to be favorable in patients carrying wild-type KRAS, TP53, and SMAD4. Besides, a nomogram exhibited appreciable reliability for clinical application in predicting the prognosis of patients. Finally, the relationship between the GInLncSig model and the immune landscape in PC reflected its application value in clinical immunotherapy.

Conclusion: In summary, the GILncSig identified by us may serve as novel prognostic biomarkers, and could have a crucial role in immunotherapy decisions for PC patients.
Case report: The MSI-L/p-MMR metastatic rectal cancer patient who failed systemic therapy responds to anti-PD-1 immunotherapy after stereotactic body radiation-therapy
Authors: Liu Shijin , Zhang Yiran , Lin Yujian , Wang Peize , Pan Yunlong
Published: September 2022

Background

Traditionally, patients with microsatellite stability (MSS)/microsatellite instability-Low (MSI-L)/proficient mismatch repair (p-MMR) metastatic colorectal cancer (mCRC) have had poor benefit from immunotherapy. Therefore, how to enhance the response of immunotherapy is still a challenge for MSS/MSI-L/p-MMR CRC patient.

Case presentation

We report a special case of a rectal cancer patient with programmed death-ligand 1 (PD-L1) negative expression, MSI-L/p-MMR, tumor mutational burden-low (TMB-L) and liver metastases, who partial response (PR) to immunotherapy after systemic therapy failure including chemotherapy, anti-angiogenesis therapy and stereotactic body radiation-therapy (SBRT). The computed tomography (CT) results showed that among three liver metastases had been reduction or disappearance after Tislelizumab treatment for three times. Besides, the carcinoembryonic antigen (CEA) and carbohydrate antigen 199 (CA199) decrease and maintained at a low level for 3 months. The progression-free survival (PFS) of patient has exceeded 3 months.

Conclusions

This case indicates that the patient with MSI-L/p-MMR mCRC can respond to anti-PD-1 immunotherapy after systemic therapy. And the SBRT (targeting liver metastases) may a method for increase-sensitivity of immunotherapy in CRC patients with MSI-L/p-MMR.
Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks
Authors: Kraft Kaisa , Velhonoja Otso , Eerola Tuomas , Suikkanen Sanna , Tamminen Timo , Haraguchi Lumi , Ylöstalo Pasi , Kielosto Sami , Johansson Milla , Lensu Lasse , Kälviäinen Heikki , Haario Heikki , Seppälä Jukka
Published: September 2022

Plankton communities form the basis of aquatic ecosystems and elucidating their role in increasingly important environmental issues is a persistent research question. Recent technological advances in automated microscopic imaging, together with cloud platforms for high-performance computing, have created possibilities for collecting and processing detailed high-frequency data on planktonic communities, opening new horizons for testing core hypotheses in aquatic ecosystems. Analyzing continuous streams of big data calls for development and deployment of novel computer vision and machine learning systems. The implementation of these analysis systems is not always straightforward with regards to operationality, and issues regarding data flows, computing and data treatment need to be considered. We created a data pipeline for automated near-real-time classification of phytoplankton during remote deployment of imaging flow cytometer (Imaging FlowCytobot, IFCB). Convolutional neural network (CNN) is used to classify continuous imaging data with probability thresholds used to filter out images not belonging to our existing classes. The automated data flow and classification system were used to monitor dominating species of filamentous cyanobacteria on the coast of Finland during summer 2021. We demonstrate that good phytoplankton recognition can be achieved with transfer learning utilizing a relatively shallow, publicly available, pre-trained CNN model and fine-tuning it with community-specific phytoplankton images (overall F1-score of 0.95 for test set of our labeled image data complemented with a 50% unclassifiable image portion). This enables both fast training and low computing resource requirements for model deployment making it easy to modify and applicable in wide range of situations. The system performed well when used to classify a natural phytoplankton community over different seasons (overall F1-score 0.82 for our evaluation data set). Furthermore, we address the key challenges of image classification for varying planktonic communities and analyze the practical implications of confused classes. We published our labeled image data set of Baltic Sea phytoplankton community for the training of image recognition models (~63000 images in 50 classes) to accelerate implementation of imaging systems for other brackish and freshwater communities. Our evaluation data set, 59 fully annotated samples of natural communities throughout an annual cycle, is also available for model testing purposes (~150000 images).
Deeper diversity exploration: New Typhlotanaidae (Crustacea: Tanaidacea) from the Kuril-Kamchatka Trench area
Authors: Gellert Marta , Palero Ferran , Błażewicz Magdalena
Published: September 2022

Typhlotanaidae Sieg, 1984, is one of the most diverse Tanaidacea families from deep-sea waters. Its diversity is underestimated, and evolutionary relationships within the family remain mostly unknown. Deep-sea typhlotanaids collected from 23 sites across the Kuril-Kamchatka Trench and nearby waters were studied using an integrative taxonomy approach, combining morphological and genetic data (i.e., the mitochondrial subunit I of the cytochrome oxidase (COI) and the 18S rDNA nuclear gene). One new species ofTyphlamiaand two new species belonging to two new genera are described, significantly increasing the known diversity of typhlotanaids from the NW Pacific. The molecular phylogeny obtained, despite being preliminary results, was congruent with morphological data and supports the monophyly of different groups such as the ‘short-bodied’ forms (represented byTy. cornutusandTy. eximius) or the ‘collar’ forms (e.g.,Ty. variabilisandTorquella). Molecular data confirm the non-monophyly ofTyphlotanaisspecies. Finally, the new typhlotanaid taxa seem to have distinct bathymetric distribution and ecological requirements, but further data on environmental factors and species abundances are still needed.
Arctic biogeochemical and optical properties of dissolved organic matter across river to sea gradients
Authors: Novak Michael G. , Mannino Antonio , Clark J. Blake , Hernes Peter , Tzortziou Maria , Spencer Robert G. M. , Kellerman Anne M. , Grunert Brice
Published: September 2022

Arctic landscapes are warming and becoming wetter due to changes in precipitation and the timing of snowmelt which consequently alters seasonal runoff and river discharge patterns. These changes in hydrology lead to increased mobilization and transport of terrestrial dissolved organic matter (DOM) to Arctic coastal seas where significant impacts on biogeochemical cycling can occur. Here, we present measurements of dissolved organic carbon (DOC) and chromophoric DOM (CDOM) in the Yukon River-to-Bering Sea system and two river plumes on the Alaska North Slope which flow into the Beaufort Sea. Our sampling characterized optical and biogeochemical properties of DOM during high and low river discharge periods for the Yukon River-Bering Sea system. The average DOC concentration at the multiple Yukon River mouths ranged from a high of 10.36 mg C L-1 during the ascending limb of the 2019 freshet (late May), 6.4 mg C L-1 during the descending limb of the 2019 freshet (late June), and a low of 3.86 mg C L-1 during low river discharge in August 2018. CDOM absorption coefficient at 412 nm (aCDOM(412)) averaged 8.23 m-1, 5.07 m-1, and 1.9 m-1, respectively. Several approaches to model DOC concentration based on its relationship with CDOM properties demonstrated cross-system seasonal and spatial robustness for these Arctic coastal systems despite spanning an order of magnitude decrease in DOC concentration from the lower Yukon River to the Northern Bering Sea as well as the North Slope systems. “Snapshot” fluxes of DOC and CDOM across the Yukon River Delta to Norton Sound were calculated from our measurements and modeled water fluxes forced with upstream USGS river gauge data. Our findings suggest that during high river flow, DOM reaches the delta largely unaltered by inputs or physical and biogeochemical processing and that the transformations of Yukon River DOM largely occur in the plume. However, during low summer discharge, multiple processes including local precipitation events, microbial decomposition, photochemistry, and likely others can alter the DOM properties within the lower Yukon River and Delta prior to flowing into Norton Sound.