Miracle-dz/UniFAR-FTUs huggingface dataset:
Breast microbiome associations with breast tumor characteristics and neoadjuvant chemotherapy: A case-control study

Background Commensal microbiota have been proven to colonize the mammary gland, but whether their composition is altered in patients with breast cancer (BC) remains elusive. This study intends to explore the breast microbiome differences between benign and malignant diseases and to investigate the impact of neoadjuvant chemotherapy (NAC) on the breast microbiota in patients with BC. Methods Breast normal adipose tissues (NATs) were collected from 79 patients with BC and 15 controls between July 2019 and November 2021. The BC group consisted of 29 patients who had received NAC and 50 who were non-NAC patients. Participants diagnosed with benign breast disease were recruited as controls. 16S rRNA gene sequencing was used to analyze the bacterial diversity of NATs. Results The community structure of the NAT microbiome was significantly different between the BC and control groups. Proteobacteria decreased (47.40% versus 39.74%), whereas Firmicutes increased (15.71% versus 25.33%) in patients with BC when compared with that in control tissues. Nine genera were enriched in BC NATs, and four genera levels increased in the control group. The associations between differential bacterial genera and breast tumor grade were calculated by Spearman’s correlation. The results showed that tumor grade was positively associated with the relative abundance of Streptococcus and negatively related to Vibrio, Pseudoalteromonas, RB41, and Photobacterium. Moreover, menopause was associated with the microbiota composition change of non-NAC BC patients and related to the significant reduction in the abundance level of Pseudoalteromonas, Veillonella, and Alcaligenes. In addition, NAC was related to the beta diversity of patients with BC and associated with the decrease of Clostridium_sensu_stricto_7 and Clostridium_sensu_stricto_2 in postmenopausal patients. Of note, Tax4Fun functional prediction analysis revealed that the metabolic state was more exuberant in the BC group with upregulating of multiple metabolism-related pathways. Conclusion Our results offer new insight into the relationship between NAC and breast microbiota and help to better characterize the breast microbial dysbiosis that occurs in patients with BC. Further epidemiological studies with larger sample size and well-designed animal experiments are required to elucidate the role of breast microbiota in the therapeutic outcome of BC.
Drug repurposing candidates to treat core symptoms in autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by high heritability and clinical heterogeneity. The main core symptoms are social communication deficits. There are no medications approved for the treatment of these symptoms, and medications used to treat non-specific symptoms have serious side effects. To identify potential drugs for repurposing to effectively treat ASD core symptoms, we studied ASD risk genes within networks of protein-protein interactions of gene products. We first defined an ASD network from network-based analyses, and identified approved drugs known to interact with proteins within this network. Thereafter, we evaluated if these drugs can change ASD-associated gene expression perturbations in genes in the ASD network. This was done by analyses of drug-induced versus ASD-associated gene expression, where opposite gene expression perturbations in drug versus ASD indicate that the drug could counteract ASD-associated perturbations. Four drugs showing significant (p < 0.05) opposite gene expression perturbations in drug versus ASD were identified: Loperamide, bromocriptine, drospirenone, and progesterone. These drugs act on ASD-related biological systems, indicating that these drugs could effectively treat ASD core symptoms. Based on our bioinformatics analyses of ASD genetics, we shortlist potential drug repurposing candidates that warrant clinical translation to treat core symptoms in ASD.
GamReg Sweden—Protocol for a systematic cohort data collection for improved clinical knowledge in specialized gambling disorder treatment

Background Gambling disorder is the first non-substance-related addiction which is recognized as a diagnostic entity and assessed in treatment settings. However, in many clinical settings, assessment, and structured treatment for this condition is severely under-developed, and treatment seeking in many settings is low. This is a protocol paper describing the rationale and structure of a recently established quality register, allowing for structured monitoring of treatment seeking, treatment needs and treatment provision in Swedish health care settings, for gambling disorder and associated conditions. Methods Since 2019, a Swedish quality register is in use for the systematic data collection from patients receiving treatment in specialized health care. The register is held by Region Skåne, and approved for national use. Swedish quality registers allow for the clinical monitoring of treatment uptake and needs, for quality improvement purposes, and collect systematic cohort data for these purposes. In addition, these quality registers potentially allow for future research projects, after separate ethics applications, allowing for clinical follow-up studies based on non-identified quality register data. Clinical challenges and research knowledge gaps are addressed in the present register, including mental health comorbidity, history of suicidal behavior, comorbid alcohol, drugs and gaming behaviors, and fundamental psycho-social variables such as violence victimization, concerned significant others including children's situation in families of problem gamblers, and main income and involvements with social services and enforcement agency. In addition, patient flows, including rates of referral from primary care and other treatment settings, can be followed. The overall quality register project is registered at clinicaltrials.gov (NCT05276193). Discussion The present protocol paper will allow for systematic reporting and future projects addressing knowledge gaps in clinical treatment for gambling disorder, and highlight the importance for evidence-based treatment in a behavioral addiction. Importantly, the current data will contribute to a better understanding of which patient groups may be less likely to seek or to be referred to treatment, and thereby may shape future initiatives to increase screening and referral in targeted, vulnerable groups.
Fortification of diets with omega-3 long-chain polyunsaturated fatty acids enhances feedlot performance, intramuscular fat content, fat melting point, and carcass characteristics of Tattykeel Australian White MARGRA lambs

Meat eating quality indices such as intramuscular fat content (IMF) and fat melting point (FMP) of the Longissimus thoracis et lumborum muscle and the feedlot performance, carcass traits, and commercial wholesale cuts of lot-fed Tattykeel Australian White (TAW) MARGRA lambs as a result of dietary fortification of the diet with omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) were evaluated. A total of 75 TAW MARGRA lambs at 6 months of age with an average liveweight of 30 ± 1.2 kg were used. The lambs were randomly allocated to the following three dietary treatments of 25 lambs each in a 47-day feeding trial using a completely randomized experimental design: (1) control diet of hay plus pellets without omega-3 oil, (2) hay plus commercial whole grain pellets (MSM) without omega-3 oil, and (3) hay plus pellets fortified with omega-3 oil. It was hypothesized that dietary supplementation with omega-3 fortified pellets will improve feedlot performance, meat-eating quality indices of IMF, FMP, and carcass characteristics. Lot-fed lambs on the MSM whole grain had the highest feed intake of 1.69 kg/day, followed by the control at 1.57 kg/day and the lowest in the omega-3 diet at 1.01 kg/day (p = 0.0001). However, the omega-3 diet had the highest average daily gain of 230 g/head/day (p = 0.0001), indicating the greatest feed efficiency since it had the best growth response with minimal feed intake. Post-slaughter evaluation of the Longissimus thoracis et lumborum muscle revealed significant treatment variations in IMF (p = 0.0001), FMP (p = 0.0001), pH (p = 0.0380), and wholesale French rack primal cut (p = 0.0001). Strong correlations (p < 0.05) between liveweight, temperature, pH, FMP, and IMF were observed. Similarly, significant correlations between carcass characteristics of total saleable meat yield, lean trim, fat trims, bones, and leg shank were evident (p < 0.05). However, there were no treatment differences in the final liveweight, GR fat depth, hot standard carcass weight, or dressing percentage. The findings indicate that feedlot performance, meat-eating quality traits such as IMF and FMP, and commercial wholesale French rack cuts can be further improved during feedlot finishing of TAW MARGRA lambs through dietary supplementation with omega-3 oils, and hence the tested hypothesis of improved meat quality attributes is partially confirmed.
Set Based Analysis of Arithmetic

Set based analysis is an approach to compile-time program analysis that is based on a simple approximation: all dependencies between variables are ignored. In effect, program variables are treated as sets of values. Thus far, set based analysis techniques have focussed on data-constructor languages. The main reason for this is algorithmic: the equality for data-constructor values is structural (that is, two values f(v1, ., vn) and f''(v1'', ., vn'') are equal if and only if f and f'' are identical constructors and vi = vi'', i = 1.n). This has important implications for how sets of such values can be represented during the computation of a set based analysis. In contrast, the equality theory of arithmetic is much richer. Two terms with very different structure can be equal. Correspondingly, the manipulation and representation of sets of arithmetic values is significantly more complex. In this paper we extend the ideas of set based analysis to arithmetic expression in such a way that the analysis yields descriptions of how arithmetic values are computed. Importantly, this extended analysis yields useful information about the arithmetic components of a program while maintaining the efficiency of the basic set constraint approach. We show how this information can be exploited during compilation with two examples involving array bounds elimination. While this work is carried out in the context of the ML, the techniques developed appear to be applicable to other languages.
An empirical analysis of talent policy, executive incentive, and enterprise green technological innovation based on China’s A-share listed companies

This article investigates how talent policies affect corporate green technological innovation through executive incentive strategies based on signaling theory and principal-agent theory, by examining samples from 1,536 A-share listed companies between 2010 and 2020. The findings indicate that talent policy helps enterprises boost green technological innovation while accelerating it by improving executive compensation incentives. This effect path is more significant in high-tech enterprises and enterprises with weak solvency ratios. However, we find that the current talent policy has inhibited the green innovation of enterprises. The conclusions provide micro-evidence for the impact mechanism by which talent policy affects enterprise green technological innovation and offer scientifically based guidelines for optimizing talent policy to promote innovation-driven development strategy.
Review of the input-output network and its application in energy and mineral industries

Nowadays, it has become a widespread consensus to deal with global warming through carbon emission reduction among mainstream scientists in the world. As the main battlefield and main force to achieve carbon peak and carbon neutrality, the energy and mineral industries play a crucial role. At the same time, as the basic industries provide energy and raw materials, the energy and mineral industries and other industries form a complex and integrated economic system with each other through input-output correlation. It can provide scientific reference for policymakers and market investors to quantitatively reveal the overall structure of the industry and deeply analyze the role and position of energy and mineral industries in it. Combining the input-output analysis with the complex network theory, the input-output network is a set of theoretical methods with strong theory and application to describe the industrial association structure both between economies and within them, and a powerful tool for studying linked character between energy and mineral industries and related industries, carbon emission, environmental protection and so on from the perspective of physical economics. Based on document analysis, this paper introduces the concept and theoretical basis of the input-output network and energy and mineral industries, and then systematically expounds the research status of the input-output network from several dimensions such as data source, research object, and research question. Finally, the paper summarizes research methods, research objects, and application scope of the input-output network, points out the weak links, and prospects some future development directions in energy and mineral industries.
Executive functions mediate the association between ADHD symptoms and anxiety in a clinical adolescent population

Objective Attention-deficit/hyperactivity disorder (ADHD) is associated with a high prevalence of anxiety disorders in children and adolescents. The reasons for this association are poorly understood. Preliminary findings with young adults have suggested that executive functions and functional impairment may mediate the relationship between symptoms of ADHD and mixed anxiety and depressive symptoms. The objective of this study was to explore whether ADHD symptoms, executive functions and functional impairment predict anxiety in a clinical adolescent population. In addition, we investigated the possible mediating role of executive functions and functional impairment in this relationship. Method One hundred adolescents with ADHD and their parents completed the ADHD Rating Scale IV (ADHD RS-IV), the Behavior Rating Inventory of Executive Function (BRIEF), and the Weiss Functional Impairment Rating Scale (WFIRS) in relation to an RCT study. The adolescents also completed the Screen for Child Anxiety-Related Emotional Disorders (SCARED). Analyses were conducted using regression and a serial multiple mediator model. Results In the regression analyses, parent-rated ADHD symptoms were unable to predict anxiety, but ADHD inattention symptoms predicted anxiety in the self-ratings. Executive dysfunction and functional impairment predicted anxiety in both the parent- and self-reports. In the mediation analyses ADHD symptoms alone did not predict anxiety, but executive dysfunction mediated this relationship as expected. Functional impairment mediated this relationship indirectly through executive functions. The results were similar in the parent- and self- reports. Conclusion The results pinpoint executive dysfunction as an important treatment target for alleviating anxiety in adolescents with impairing ADHD symptoms.
Mucosal nanobody IgA as inhalable and affordable prophylactic and therapeutic treatment against SARS-CoV-2 and emerging variants

Anti-COVID antibody therapeutics have been developed but not widely used due to their high cost and escape of neutralization from the emerging variants. Here, we describe the development of VHH-IgA1.1, a nanobody IgA fusion molecule as an inhalable, affordable and less invasive prophylactic and therapeutic treatment against SARS-CoV-2 Omicron variants. VHH-IgA1.1 recognizes a conserved epitope of SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and potently neutralizes major global SARS-CoV-2 variants of concern (VOC) including the Omicron variant and its sub lineages BA.1. 1, BA.2 and BA.2. 12.1. VHH-IgA1.1 is also much more potent against Omicron variants as compared to an IgG Fc fusion construct, demonstrating the importance of IgA mediated mucosal protection for Omicron infection. Intranasal administration of VHH-IgA1.1 prior to or after challenge conferred significant protection from severe respiratory disease in K18-ACE2 transgenic mice infected with SARS-CoV-2 VOC. More importantly, for cost-effective production, VHH-IgA1.1 produced in Pichia pastoris had comparable potency to mammalian produced antibodies. Our study demonstrates that intranasal administration of affordably produced VHH-IgA fusion protein provides effective mucosal immunity against infection of SARS-CoV-2 including emerging variants.
Bcl-3 regulates the function of Th17 cells through raptor mediated glycolysis metabolism

Bcl-3 is an atypical IκB family member that regulates transcription in the nucleus by binding to the p50/p52 homologous dimer subunit. Although various studies illustrate the important role of Bcl-3 in physiological function, its role in metabolism is still unclear. We found that Bcl-3 has a metabolic regulatory effect on autoimmunity. Bcl-3-depleted mice are unable to develop experimental autoimmune encephalomyelitis. The disease resistance was linked to an increase in lactate levels in Th17 cells, and lactate could alleviate EAE development in WT mice. Bcl-3 deficient mice had more differentiated Th17 cells and an increased extracellular acidification rate in these cells. Concurrently, their ultimate respiration rate and respiratory reserve capacity were significantly lower than wild-type mice. However, adding GNE-140 (LADH inhibitor) to Bcl-3-deficient Th17 cells could reverse the phenomenon, and lactate supplementation could increase the glycolysis metabolism of Th17 cells in WT mice. Mechanically, Bcl-3 could interact with Raptor through ANK and RNC domains. Therefore, Bcl-3 regulates Th17 pathogenicity by promoting Raptor mediated energy metabolism, revealing a novel regulation of adaptive immunity.
Intravital imaging of hemodynamic glomerular effects of enalapril or/and empagliflozin in STZ-diabetic mice

Background: Diabetic kidney disease is the leading cause of end-stage renal disease. Administration of ACE inhibitors or/and SGLT2 inhibitors show renoprotective effects in diabetic and other kidney diseases. The underlying renoprotective mechanisms of SGLT2 inhibition, especially in combination with ACE inhibition, are incompletely understood. We used longitudinal intravital microscopy to directly elucidate glomerular hemodynamics on a single nephron level in response to the ACE inhibitor enalapril or/and the SGLT2 inhibitor empagliflozin. Methods: Five weeks after the induction of diabetes by streptozotocin, male C57BL/6 mice were treated with enalapril, empagliflozin, enalapril/empagliflozin or placebo for 3 days. To identify hemodynamic regulation mechanisms, longitudinal intravital multiphoton microscopy was employed to measure single nephron glomerular filtration rate (snGFR) and afferent/efferent arteriole width. Results: Diabetic mice presented a significant hyperfiltration. Compared to placebo treatment, snGFR was reduced in response to enalapril, empagliflozin, or enalapril/empagliflozin administration under diabetic conditions. While enalapril treatment caused significant dilation of the efferent arteriole (12.55 ± 1.46 µm vs. control 11.92 ± 1.04 µm, p < 0.05), empagliflozin led to a decreased afferent arteriole diameter (11.19 ± 2.55 µm vs. control 12.35 ± 1.32 µm, p < 0.05) in diabetic mice. Unexpectedly under diabetic conditions, the combined treatment with enalapril/empagliflozin had no effects on both afferent and efferent arteriole diameter change. Conclusion: SGLT2 inhibition, besides ACE inhibition, is an essential hemodynamic regulator of glomerular filtration during diabetes mellitus. Nevertheless, additional mechanisms—independent from hemodynamic regulation—are involved in the nephroprotective effects especially of the combination therapy and should be further explored in future studies.
Multidimensional energy poverty and depression among China's older adults

Older adults often face more pronounced energy inequality in their daily lives, which is one of the reasons for their accumulation of stress or anxiety and may further aggravate their depression. Analyzing the relationship between energy poverty and the depression level of China's older adults will provide policy enlightenment for solving the problems of older adults' relative poverty, energy poverty, and mental poverty and thus promote happy and healthy aging. In this paper, using the data of China Health and Retirement Longitudinal Study in 2018, we used the entropy weighting method to objectively assign weights to 10 indicators reflecting the status of energy poverty and construct a multidimensional energy poverty index for older adults. First, we analyzed the relationship between multidimensional energy poverty and the depression levels of older adults using multiple linear regression model and quantile regression models. Next, we used instrumental variable linear regression model and instrumental variable quantile regression models for endogeneity tests. Then, we performed a robustness check by replacing the core explanatory variable. After that, we conducted heterogeneity analyses by residential area, type of residence, and solitary status. Finally, we analyzed the mediating role of life satisfaction using structural equation modeling. Multidimensional energy poverty has aggravated depression among older adults, and the effect is greater for older adults with higher depression levels. The effect of multidimensional energy poverty on depression is greater for older adults in western China, urban areas, and those who live alone. Multidimensional energy poverty has aggravated depression among older adults by reducing their life satisfaction.
Consistency and asymptotic normality of an approximate maximum likelihood estimator for discretely observed diffusion processes

Most often the likelihood function based on discrete observations of a diffusion process is unknown, and estimators alternative to the well-behaved maximum likelihood estimator must be found. Traditionally, such estimators are defined with origin in the theory for continuous observation of the diffusion process, and are as a consequence strongly biased unless the discrete observation time-points are close. In contrast to these estimators, an estimator based on an approximation to the (unknown) likelihood function was proposed in Pedersen (1994). We prove consistency and asymptotic normality of this estimator with no assumptions on the distance between the discrete observation time-points.
Quick detection of Carassius auratus herpesvirus (CaHV) by recombinase-aid amplification lateral flow dipstick (RAA-LFD) method

Crucian carp (Carassius auratus) is one of the major freshwater species and is also a common food fish in China. Recently, Carassius auratus herpesvirus (CaHV) could induce fatal viral disease with high mortality of crucian carp, which had caused huge economic losses. In this study, we described a rapid and simple recombinase-aid amplification (RAA) assay coupled with lateral flow dipstick (LFD), which could achieve sensitive diagnosis of tumor necrosis factor receptor (TNFR) of CaHV within 35 min at 40°C. Our RAA-LFD method had a satisfactory detection limit of 100 gene copies per reaction, which was 100-fold more sensitive than traditional PCR. In addition, no cross-reaction was observed with other viral pathogens, including koi herpesvirus (KHV), cyprinid herpesvirus 2 (CyHV-2), infectious hematopoietic necrosis virus (IHNV), spring viremia of carp virus (SVCV) and grass carp reovirus (GCRV). Furthermore, the overall cost of the method was cut in half compared to previous studies. In conclusion, RAA-LFD assay is therefore, a promising alternative for point-of-care testing (POCT) of CaHV, which is feasible and of certain value in application of aquatic disease control.