Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Safety of Shenfu Injection for Severe Pneumonia in the Elderly: A Systematic Review and Meta-Analysis Based on Western and Eastern Medicine

Background: Although increasing clinical trials studying Shenfu injection (SFI) comprising panaxoside 0.8 mg/ml extracted from Panax ginseng C.A. Mey. and aconitine 0.1 mg/ml extracted from Aconitum carmichaeli Debeaux for elderly patients with severe pneumonia on biomarkers associated with COVID-19 progression are emerging, there is no evidence-based evaluation for the effect of SFI on elderly severe pneumonia. Objectives: To evaluate the effect of SFI on elderly patients with severe pneumonia providing hints for treating critical COVID-19, we conducted a systematic review and meta-analysis. Methods: Nine databases, namely, PubMed, EMBASE, Web of Science, Science Direct, Google Scholar, Wanfang, Chongqing VIP Database, CNKI, and SinoMed were used to search clinical trials reporting the effect of SFI as an adjuvant for elderly severe pneumonia on outcomes of interest. Primary outcomes were total effective rate, Acute Physiology and Chronic Health Evaluation (APACHE) II score, mortality, and safety. Secondary outcomes were predictors associated with COVID-19 progression. Duplicated or irrelevant articles with unavailable data were excluded. Cochrane Collaboration’s tool was used to evaluate the risk of bias by two reviewers independently. All data were analyzed by Rev Man 5.4. Continuous variables were shown as weighted mean difference (WMD) or standard mean difference (SMD) with 95% confidence intervals (95% CI), whereas dichotomous data were calculated as the risk ratio (RR) with 95% CI. Results: We included 20 studies with 1, 909 participants, and the pooled data showed that compared with standard control, SFI could improve the total effective rate (RR = 1.25, 95% CI = 1.14–1.37, and n = 689), APACHE II score (WMD = −2.95, 95% CI = −3.35, −2.56, and n = 809), and predictors associated with COVID-19 progression (brain natriuretic peptide, creatine kinase, stroke volume, cardiac output, left ventricular ejection fraction, cardiac index, sE-selectin, von Willebrand factor, activated partial thromboplastin time, platelet counts, D-Dimer, procalcitonin, and WBC count). SFI may reduce mortality (RR = 0.52, 95% CI = 0.37–0.73, and n = 429) and safety concerns (RR = 0.29, 95% CI = 0.17–0.51, and n = 150) for elderly severe pneumonia. Conclusion: SFI as an adjuvant may improve the total effective rate, APACHE II score, gas exchange, and predictors associated with COVID-19 progression, reducing mortality and safety concerns for elderly patients with severe pneumonia.
Use of DNA pools of a reference population for genomic selection of a binary trait in Atlantic salmon

Genomic selection has a great potential in aquaculture breeding since many important traits are not directly measured on the candidates themselves. However, its implementation has been hindered by staggering genotyping costs because of many individual genotypes. In this study, we explored the potential of DNA pooling for creating a reference population as a tool for genomic selection of a binary trait. Two datasets from the SalmoBreed population challenged with salmonid alphavirus, which causes pancreas disease, were used. Dataset-1, that includes 855 individuals (478 survivors and 377 dead), was used to develop four DNA pool samples (i.e., 2 pools each for dead and survival). Dataset-2 includes 914 individuals (435 survivors and 479 dead) belonging to 65 full-sibling families and was used to develop in-silico DNA pools. SNP effects from the pool data were calculated based on allele frequencies estimated from the pools and used to calculate genomic breeding values (GEBVs). The correlation between SNP effects estimated based on individual genotypes and pooled data increased from 0.3 to 0.912 when the number of pools increased from 1 to 200. A similar trend was also observed for the correlation between GEBVs, which increased from 0.84 to 0.976, as the number of pools per phenotype increased from 1 to 200. For dataset-1, the accuracy of prediction was 0.71 and 0.70 when the DNA pools were sequenced in 40× and 20×, respectively, compared to an accuracy of 0.73 for the SNP chip genotypes. For dataset-2, the accuracy of prediction increased from 0.574 to 0.691 when the number of in-silico DNA pools increased from 1 to 200. For this dataset, the accuracy of prediction using individual genotypes was 0.712. A limited effect of sequencing depth on the correlation of GEBVs and prediction accuracy was observed. Results showed that a large number of pools are required to achieve as good prediction as individual genotypes; however, alternative effective pooling strategies should be studied to reduce the number of pools without reducing the prediction power. Nevertheless, it is demonstrated that pooling of a reference population can be used as a tool to optimize between cost and accuracy of selection.
PARP inhibitor resistance in breast and gynecological cancer: Resistance mechanisms and combination therapy strategies

Breast cancer and gynecological tumors seriously endanger women’s physical and mental health, fertility, and quality of life. Due to standardized surgical treatment, chemotherapy, and radiotherapy, the prognosis and overall survival of cancer patients have improved compared to earlier, but the management of advanced disease still faces great challenges. Recently, poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis) have been clinically approved for breast and gynecological cancer patients, significantly improving their quality of life, especially of patients with BRCA1/2 mutations. However, drug resistance faced by PARPi therapy has hindered its clinical promotion. Therefore, developing new drug strategies to resensitize cancers affecting women to PARPi therapy is the direction of our future research. Currently, the effects of PARPi in combination with other drugs to overcome drug resistance are being studied. In this article, we review the mechanisms of PARPi resistance and summarize the current combination of clinical trials that can improve its resistance, with a view to identify the best clinical treatment to save the lives of patients.
DNA methylation regulators-related molecular patterns and tumor immune landscape in hepatocellular carcinoma

Increasing evidence showed that the dysregulation of DNA methylation regulators is a decisive feature of almost all cancer types and affects tumor progressions. However, few studies focused on the underlying influences of DNA methylation regulators-related genes (DMRegs) in immune cell-infiltration characteristics, tumor microenvironment (TME) and immunotherapy in HCC patients. In our study, the alterations of DNA methylation regulators modification patterns (DMRPs) were clustered from hepatocellular carcinoma (HCC) samples based on the expression of DNA methylation regulators as well as genetic and transcriptional features. In addition, based on molecular identification of three distinct molecular subtypes, we found that different DMRPs alterations were related to different clinicopathological characteristics, prognosis, and immune cells infiltration features. Moreover, we constructed and validated a DNA methylation regulators-related genes score (DMRegs_score) to predict the survival of HCC patients. A high DMRegs _score, which was characterized by more TP53 wild mutation, high expression of PD-1, CTLA-4, and remarkable immunity activation, was indicative of poor prognosis. Furthermore, we validated the expression of eight genes which were used for the prognostic signature in this risk score by RT-qPCR using tissues from our center. More importantly, DMRegs_score was highly correlated with targeted drug sensitivity. Additionally, we developed a highly accurate scoring system that could be used to improve the clinical applicability of DMRegs _score. In conclusion, these findings may contribute to a better understanding of DNA methylation regulators and provide new strategies for evaluating prognosis and developing more effective combination therapy for HCC patients.
Genetic diversity and population structure of Tongcheng pigs in China using whole-genome SNP chip

Tongcheng (TC) pigs, distinguished by their superior meat quality, are a Chinese indigenous pig breed. Recently, the genetic resources of TC pigs are under tremendous threat due to the introduction of cosmopolitan pig breeds and African swine fever disease. To promote their management and conservation, the present study assessed genetic diversity and population structure of TC pigs using single nucleotide polymorphism (SNP) markers. A total of 26, 999 SNPs were screened from 51, 315 SNPs in 68 TC pigs. The multi-dimensional scaling (MDS) analysis and neighbor-joining tree revealed that all 68 pigs were from a purebred population. The effective population size decreased over time, and it was 96 prior to generation 20. Both linkage disequilibrium (LD) and neutrality test indicated a low selection of TC pigs with average LD value of 0.15 ± 0.23. Genetic diversity results exhibited a minor allele frequency (MAF) of 0.23, observed heterozygosity (HO) of 0.32, expected heterozygosity (He) of 0.31, and nucleotide diversity (Pi) of 0.31. All these parameters indicated a remarkably high genetic diversity of TC pigs. Additionally, 184 runs of homozygosity (ROH) segments were detected from the whole genome of TC pigs with an average ROH length of 23.71Mb, ranging from 11.26Mb to 69.02 Mb. The highest ROH coverage was found on chromosome 1 (10.12%), while the lowest was on chromosome 18 (1.49%). The average inbreeding coefficients based on ROH (FROH) was 0.04%. Fourteen ROH islands containing 240 genes were detected on 9 different autosomes. Some of these 240 genes were overlapped with the genes related to biological processes such as immune function, reproduction, muscular development, and fat deposition, including FFAR2, FFAR4, MAPK8, NPY5R, KISS1, and these genes might be associated with such traits as meat quality and disease resistance in TC pigs. Taken together, population structure and genetic diversity results suggested that the TC pig represented a valuable genetic resource. However, TC pig breed conservation program remains to be further optimized to ensure adequate genetic diversity and avoid inbreeding depression. Our findings provide theoretical basis for formulating management and conservation strategies for TC pigs.
Affective video recommender systems: A survey

Traditional video recommendation provides the viewers with customized media content according to their historical records (e.g., ratings, reviews). However, such systems tend to generate terrible results if the data is insufficient, which leads to a cold-start problem. An affective video recommender system (AVRS) is a multidiscipline and multimodal human-robot interaction (HRI) system, and it incorporates physical, physiological, neuroscience, and computer science subjects and multimedia resources, including text, audio, and video. As a promising research domain, AVRS employs advanced affective analysis technologies in video resources; therefore, it can solve the cold-start problem. In AVRS, the viewers’ emotional responses can be obtained from various techniques, including physical signals (e.g., facial expression, gestures, and speech) and internal signals (e.g., physiological signals). The changes in these signals can be detected when the viewers face specific situations. The physiological signals are a response to central and autonomic nervous systems and are mostly involuntarily activated, which cannot be easily controlled. Therefore, it is suitable for reliable emotion analysis. The physical signals can be recorded by a webcam or recorder. In contrast, the physiological signals can be collected by various equipment, e.g., psychophysiological heart rate (HR) signals calculated by echocardiogram (ECG), electro-dermal activity (EDA), and brain activity (GA) from electroencephalography (EEG) signals, skin conductance response (SCR) by a galvanic skin response (GSR), and photoplethysmography (PPG) estimating users’ pulse. This survey aims to provide a comprehensive overview of the AVRS domain. To analyze the recent efforts in the field of affective video recommendation, we collected 92 relevant published articles from Google Scholar and summarized the articles and their key findings. In this survey, we feature these articles concerning AVRS from different perspectives, including various traditional recommendation algorithms and advanced deep learning-based algorithms, the commonly used affective video recommendation databases, audience response categories, and evaluation methods. Finally, we conclude the challenge of AVRS and provide the potential future research directions.
Interleukin-6-derived cancer-associated fibroblasts activate STAT3 pathway contributing to gemcitabine resistance in cholangiocarcinoma

Cancer-associated fibroblasts (CAFs) are the dominant component of the tumor microenvironment (TME) that can be beneficial to the generation and progression of cancer cells leading to chemotherapeutic failure via several mechanisms. Nevertheless, the roles of CAFs on anti-cancer drug response need more empirical evidence in cholangiocarcinoma (CCA). Herein, we examined the oncogenic roles of CAFs on gemcitabine resistance in CCA cells mediated via IL-6/STAT3 activation. Our findings showed that CCA-derived CAFs promote cell viability and enhance gemcitabine resistance in CCA cells through the activation of IL-6/STAT3 signaling. High expression of IL-6R was correlated with a poor overall survival rate and gemcitabine resistance in CCA, indicating that IL-6R can be a prognostic or predictive biomarker for the chemotherapeutic response of CCA patients. Blockade of IL-6R on CCA cells by tocilizumab, an IL-6R humanized antihuman monoclonal antibody, contributed to inhibition of the CAF-CCA interaction leading to enhancement of gemcitabine sensitivity in CCA cells. The results of this study should be helpful for modifying therapeutic regimens aimed at targeting CAF interacting with cancer cells resulting in the suppression of the tumor progression but enhancement of drug sensitivity.
Rapid identification and deployment of major genes for flowering time and awn traits in common wheat

Molecular markers are developed to accelerate deployment of genes for desirable traits segregated in a bi-parental population of recombinant inbred lines (RILs) or doubled haplotype (DH) lines for mapping. However, it would be the most effective if such markers for multiple traits could be identified in an F2 population. In this study, single nucleotide polymorphisms (SNP) chips were used to identify major genes for heading date and awn in an F2 population without developing RILs or DH lines. The population was generated from a cross between a locally adapted spring wheat cultivar “Ningmaizi119” and a winter wheat cultivar “Tabasco” with a diverse genetic background. It was found that the dominant Vrn-D1 allele could make Ningmaizi119 flowered a few months earlier than Tabasco in the greenhouse and without vernalization. The observed effects of the allele were validated in F3 populations. It was also found that the dominant Ali-A1 allele for awnless trait in Tabasco or the recessive ali-A1 allele for awn trait in Ningmaizi119 was segregated in the F2 population. The allelic variation in the ALI-A1 gene relies not only on the DNA polymorphisms in the promoter but also on gene copy number, with one copy ali-A1 in Ningmaizi119 but two copies Ali-A1 in Tabasco based on RT-PCR results. According to wheat genome sequences, cultivar “Mattis” has two copies Ali-A1 and cultivar “Spelta” has four copies Ali-A in a chromosome that was uncharacterized (ChrUN), in addition to one copy on chromosome 5A. This study rapidly characterized the effects of the dominant Vrn-D1 allele and identified the haplotype of Ali-A1 in gene copy number in the F2 segregation population of common wheat will accelerate their deployment in cycling lines in breeding.
Genome sequencing and analysis uncover the regulatory elements involved in the development and oil biosynthesis of Pongamia pinnata (L.) – A potential biodiesel feedstock

Due to rapid industrialization, the consumption of petro-products has increased, while fossil fuel resources have been gradually depleted. There has been a resurgence of interest in plant-derived biofuels as a sustainable alternative to fossil fuels for the purpose of reducing greenhouse gas emissions. Pongamia pinnata L. , which is also known as Millettia pinnata is an oil-yielding, leguminous tree with a large and complex genome. Despite its multiple industrial applications, this orphan tree species has inconsistent yields and a limited understanding of its functional genomics. We assessed physiological and morphological characteristics of five high-yielding pongamia accessions and deduced important yield descriptors. Furthermore, we sequenced the genome of this potential biofuel feedstock using Illumina HiSeq, NextSeq, and MiSeq platforms to generate paired-end reads. Around 173 million processed reads amounting to 65.2 Gb were assembled into a 685 Mb genome, with a gap rate of 0.02%. The sequenced scaffolds were used to identify 30,000 gene models, 406,385 Simple-Sequence-Repeat (SSR) markers, and 43.6% of repetitive sequences. We further analyzed the structural information of genes belonging to certain key metabolic pathways, including lipid metabolism, photosynthesis, circadian rhythms, plant-pathogen interactions, and karanjin biosynthesis, all of which are commercially significant for pongamia. A total of 2,219 scaffolds corresponding to 29 transcription factor families provided valuable information about gene regulation in pongamia. Similarity studies and phylogenetic analysis revealed a monophyletic group of Fabaceae members wherein pongamia out-grouped from Glycine max and Cajanus cajan, revealing its unique ability to synthesize oil for biodiesel. This study is the first step toward completing the genome sequence of this imminent biofuel tree species. Further attempts at re-sequencing with different read chemistry will certainly improve the genetic resources at the chromosome level and accelerate the molecular breeding programs.
Comparative analyses of the metabolite and ion concentrations in nectar, nectaries, and leaves of 36 bromeliads with different photosynthesis and pollinator types

Floral nectar contains mainly sugars as well as smaller amounts of amino acids and further compounds. The nectar composition varies between different plant species and it is related to the pollination type of the plant. In addition to this, other factors can influence the composition. Nectar is produced in and secreted from nectaries. A few models exist to explain the origin of nectar for dicotyl plant species, a complete elucidation of the processes, however, has not yet been achieved. This is particularly true for monocots or plant species with CAM photosynthesis. To get closer to such an elucidation, nectar, nectaries, and leaves of 36 bromeliad species were analyzed for sugars, starch, amino acids, and inorganic ions. The species studied include different photosynthesis types (CAM/C3), different pollination types (trochilophilous/chiropterophilous), or different live forms. The main sugars in nectar and nectaries were glucose, fructose, and sucrose, the total sugar concentration was about twofold higher in nectar than in nectaries, which suggests that sugars are actively transported from the nectaries into the nectar. The composition of amino acids in nectar is already determined in the nectaries, but the concentration is much lower in nectar than in nectaries, which suggests selective retention of amino acids during nectar secretion. The same applies to inorganic ions. Statistical analyses showed that the photosynthesis type and the pollination type can explain more data variation in nectar than in nectaries and leaves. Furthermore, the pollinator type has a stronger influence on the nectar or nectary composition than the photosynthesis type. Trochilophilous C3 plants showed significant correlations between the nitrate concentration in leaves and the amino acid concentration in nectaries and nectar. It can be assumed that the more nitrate is taken up, the more amino acids are synthesized in leaves and transported to the nectaries and nectar. However, chiropterophilous C3 plants show no such correlation, which means that the secretion of amino acids into the nectar is regulated by further factors. The results help understand the physiological properties that influence nectaries and nectar as well as the manner of metabolite and ion secretion from nectaries to nectar.
Characterization of main pulmonary artery and valve annulus region of piglets using echocardiography, uniaxial tensile testing, and a novel non-destructive technique

Characterization of cardiovascular tissue geometry and mechanical properties of large animal models is essential when developing cardiovascular devices such as heart valve replacements. These datasets are especially critical when designing devices for pediatric patient populations, as there is often limited data for guidance. Here, we present a previously unavailable dataset capturing anatomical measurements and mechanical properties of juvenile Yorkshire (YO) and Yucatan (YU) porcine main pulmonary artery (PA) and pulmonary valve (PV) tissue regions that will inform pediatric heart valve design requirements for preclinical animal studies. In addition, we developed a novel radial balloon catheter-based method to measure tissue stiffness and validated it against a traditional uniaxial tensile testing method. YU piglets, which were significantly lower weight than YO counterparts despite similar age, had smaller PA and PV diameters (7.6–9.9 mm vs. 10.1–12.8 mm). Young’s modulus (stiffness) was measured for the PA and the PV region using both the radial and uniaxial testing methods. There was no significant difference between the two breeds for Young’s modulus measured in the elastic (YU PA 84.7 ± 37.3 kPa, YO PA 79.3 ± 15.7 kPa) and fibrous regimes (YU PA 308.6 ± 59.4 kPa, YO PA 355.7 ± 68.9 kPa) of the stress-strain curves. The two testing techniques also produced similar stiffness measurements for the PA and PV region, although PV data showed greater variation between techniques. Overall, YU and YO piglets had similar PA and PV diameters and tissue stiffness to previously reported infant pediatric patients. These results provide a previously unavailable age-specific juvenile porcine tissue geometry and stiffness dataset critical to the development of pediatric cardiovascular prostheses. Additionally, the data demonstrates the efficacy of a novel balloon catheter-based technique that could be adapted to non-destructively measure tissue stiffness in situ.
Partition function of the Potts model on self-similar lattices as a dynamical system and multiple transitions

We present an analytic study of the Potts model partition function on two different types of self-similar lattices of triangular shape with non integer Hausdorff dimension. Both types of lattices analyzed here are interesting examples of non-trivial thermodynamics in less than two dimensions. First, the Sierpinski gasket is considered. It is shown that, by introducing suitable geometric coefficients, it is possible to reduce the computation of the partition function to a dynamical system, whose variables are directly connected to (the arising of) frustration on macroscopic scales, and to determine the possible phases of the system. The same method is then used to analyse the Hanoi graph. Again, dynamical system theory provides a very elegant way to determine the phase diagram of the system. Then, exploiting the analysis of the basins of attractions of the corresponding dynamical systems, we construct various examples of self-similar lattices with more than one critical temperature. These multiple critical temperatures correspond to crossing phases with different degrees of frustration.