Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, pro and anti-inflammatory cytokines interplay to orchestrate fine-tuned, dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation of inflammation. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by in silico models which enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent pro and anti-inflammatory cytokines with a focus on Tumor Necrosis Factor (TNF) and Interleukin 10 (IL-10) in lipopolysaccharide (LPS)-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform in silico experiments to disentangle the role of IL-10 feedbacks in acute inflammation. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10 – TNF switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.
Activity of estrogen receptor beta expressing neurons in the medial amygdala regulates preference towards receptive females in male mice

The processing of information regarding the sex and reproductive state of conspecific individuals is critical for successful reproduction and survival in males. Generally, male mice exhibit a preference towards sexually receptive (RF) over non-receptive females (XF) or gonadally intact males (IM). Previous studies suggested the involvement of estrogen receptor beta (ERβ) expressed in the medial amygdala (MeA) in male preference towards RF. To further delineate the role played by ERβ in the MeA in the neuronal network regulating male preference, we developed a new ERβ-iCre mouse line using the CRISPR-Cas9 system. Fiber-photometry Ca2+ imaging revealed that ERβ expressing neurons in the postero-dorsal part of the MeA (MeApd-ERβ+ neurons) were more active during social investigation towards RF compared to copresented XF or IM mice in a preference test. Chemogenetic inhibition of MeApd-ERβ+ neuronal activity abolished a preference to RF in “RF vs. XF”, but not “RF vs. IM”, tests. Analysis with cre-dependent retrograde tracing viral vectors identified the principal part of the bed nucleus of stria terminalis (BNSTp) as a primary projection site of MeApd-ERβ+ neurons. Fiber-photometry recording in the BNSTp during a preference test revealed that chemogenetic inhibition of MeApd-ERβ+ neurons abolished differential neuronal activity of BNSTp cells as well as a preference to RF against XF but not against IM mice. Collectively, these findings demonstrate for the first time that MeApd-ERβ+ neuronal activity is required for expression of receptivity-based preference (i.e., RF vs XF) but not sex-based preference (i.e., RF vs IM) in male mice. Significance Statement In this study, by introducing a new Cre mice line for ERβ+ cells, we described the function of MeApd-ERβ+ neurons and characteristics of their neuronal activity during preference tests. Using fiber photometry and DREADD techniques we have found MeApd-ERβ+ neurons have a specific role in receptivity-based (receptive female vs. non-receptive female) preference but not in sexbased (receptive female vs. intact male) preference in male mice. We have also described this specific role of MeApd-ERβ+ neurons is achieved by regulating the neuronal activity of downstream BNSTp neurons during receptivity-based, but not sex-based, preference tests. Our findings contribute to a better understating of the function of estrogen receptor expressing neurons in the neuronal network for the male-typical reproductive behaviors.
Flux exponent control predicts metabolic dynamics from network structure

Metabolic dynamics such as stability of steady states, oscillations, lags and growth arrests in stress responses are important for microbial communities in human health, ecology, and metabolic engineering. Yet it is hard to model due to sparse data available on trajectories of metabolic fluxes. For this reason, a constraint-based approach called flux control (e.g., flux balance analysis) was invented to split metabolic systems into known stoichiometry (plant) and unknown fluxes (controller), so that data can be incorporated as refined constraints, and optimization can be used to find behaviors in scenarios of interest. However, flux control can only capture steady state fluxes well, limiting its application to scenarios with days or slower timescales. To overcome this limitation and capture dynamic fluxes, this work proposes a novel constraint-based approach, flux exponent control (FEC). FEC uses a different plant-controller split between the activities of catalytic enzymes and their regulation through binding reactions. Since binding reactions effectively regulate fluxes’ exponents (from previous works), this yields the rule of FEC, that cells regulate fluxes’ exponents, not the fluxes themselves as in flux control. In FEC, dynamic regulations of metabolic systems are solutions to optimal control problems that are computationally solvable via model predictive control. Glycolysis, which is known to have minute-timescale oscillations, is used as an example to demon-strate FEC can capture metabolism dynamics from network structure. More generally, FEC brings metabolic dynamics to the realm of control system analysis and design.
Meaning-Making in the Face of Intersecting Catastrophes: COVID-19 and the Plague of Inequality

Abstract Beyond the enormous toll in illness and death, the COVID-19 pandemic unleashed multiple additional problems (job loss, evictions, hunger) that are disproportionately borne by those who were already vulnerable. In this essay, I reflect about these intersecting catastrophes, which I see as undermining the capacities of many to live meaningful and fulfilling lives. Symptoms of these problems are growing “deaths of despair” due to suicide, drug and alcohol addictions. Drawing on multidisciplinary science, I suggest that these widespread problems cannot be ministered to by focusing only at the individual level. Structural factors, including unfair distributions of resources and opportunities demand attention as well because they are fueling growing disparities between the privileged and the disadvantaged segments of contemporary societies. I examine what meanings and emotions are relevant responses to these troubled times, giving emphasis to the legitimacy of anger and outrage in the face of suffering and injustice. Further insight is sought in historical accounts of longstanding tensions between self-interest and the social contract. Going forward, I suggest that these turbulent times call for greater engagement with and scientific understanding of the arts and humanities in activating the deepest corners of our humanity. Examples from past and current art dealing with human suffering, inequality, and plagues illustrate their possible role in nurturing human capacities to understand, to care, and to act.
Variance‐based color image quantization for frame buffer display

Color image quantization is a process of representing an image with a small number of well selected colors. In this article an algorithm for multidimensional data clustering (termed the variance-based algorithm), based on the criterion of minimization of the sum-of-squared error, is applied to the problem of reducing the number of colors used to represent a given color image. The suitability of the sum-of-squared error criterion for measuring the similarity between the original and quantized images is examined using a digitized image and a computer-generated image. The experimental results indicate that this error measure is basically consistent with the perceived quality of the quantized image. The performance of the variance-based algorithm is compared with that of other algorithms for color image quantization in terms of quantization images generated using the colors selected by the variance-based and the mediancut algorithms are also presented.
Dynamic air permeability model of parachute fabrics and material parameters sensitivity analysis

Abstract To explore the effect of material parameters on dynamic air permeability of parachute fabrics, the relative porosity model was obtained by considering the yarns stretching in length and shrinking in cross-section under the transient pressure differential. A parachute fabric dynamic air permeability model with fabric material parameters was established based on the Ergun equation. The results showed that the new model is more accurate and is applicable of higher pressure differential compared with other traditional methods. On this basis, the sensitivity analysis of the effect of the fabric structural parameters and mechanical parameters on dynamic air permeability was conducted. The results showed that: (1) the dynamic air permeability decreases with increasing fabric thickness and fabric Young’s modulus, and increases with increasing fabric test area and fabric Poisson's ratio, and (2) the dynamic air permeability is more sensitive to the fabric thickness and is less sensitive to the fabric tested area, The dynamic air permeability is significantly affected by fabric Young’s modulus, but slightly affected by fabric Poisson's ratio.
Cartilaginous predictors of residual acetabular dysplasia (RAD) in developmental dysplasia of the hip following closed or open reduction: A systematic review and meta-analysis

Object This study was designed to analyze the cartilaginous predictors of residual acetabular dysplasia (RAD) after early treatment of developmental dysplasia of the hip and their diagnostic accuracy. Study design Databases such as PubMed, Embase, Cochrane, and Web of science were searched to screen the literature. The quality of the literature was assessed by the QUADAS-2 tool. Qualitative and quantitative synthesis of literature were performed based on extracted data. For quantitative synthesis studies, the sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve with corresponding confidence intervals were calculated. Results For the cartilaginous acetabular index (CAI) group, the combined values of sensitivity, specificity, and DOR were 0.80 (95% CI = 0.54–0.93), 0.73 (95% CI = 0.57–0.84), and 10.62 (95% CI = 3.96–28.53), respectively. The corresponding values in the cartilaginous center-edge angle (CCE) group were 0.71 (95% CI = 0.57–0.82), 0.78 (95% CI = 0.66–0.87), and 8.64 (95% CI = 3.08–24.25), respectively. The area under the curve (AUC) of SROC was 0.82 (95% CI = 0.78–0.85) and 0.80 (95% CI = 0.76–0.83) for the CAI and CCE groups. The CAI group had higher sensitivity, DOR, and AUC than the CCE group. Conclusion Both of these two groups have good diagnostic accuracy, and CAI/L-AI has a little edge over CCE/L-CEA. However, there is still more research needed to determine whether they can be used as independent indications for secondary orthopedic surgery. Systematic review registration: [https://www.crd. york.ac. uk/PROSPERO/], identifier: [CRD42022338332].
Locally extra-optimal regularizing algorithms

Abstract So-called local a posteriori accuracy estimates for approximate solutions of ill-posed inverse problems are under investigation. We present an approach to local a posteriori estimation along with the numerical algorithm for calculating the estimators. We analyze the local optimality in order of obtained a posteriori accuracy estimates and introduce a new important notion of locally extra-optimal regularizing algorithm as a method for the solution of ill-posed problems having optimal in order local a posteriori accuracy estimates. Finally, we demonstrate the results of numerical experiments on applications of locally extra-optimal regularizing methods, constructed on the base of Tikhonov regularization, for calculating local a posteriori accuracy estimates.
Imaging the uptake of deuterated methionine in Drosophila with stimulated Raman scattering

Introduction: Visualizing small individual biomolecules at subcellular resolution in live cells and tissues can provide valuable insights into metabolic activity in heterogeneous cells, but is challenging. Methods: Here, we used stimulated Raman scattering (SRS) microscopy to image deuterated methionine (d-Met) incorporated into Drosophila tissues in vivo. Results: Our results demonstrate that SRS can detect a range of previously uncharacterized cell-to-cell differences in d-Met distribution within a tissue at the subcellular level. Discussion: These results demonstrate the potential of SRS microscopy for metabolic imaging of less abundant but important amino acids such as methionine in tissue.
An experimental study on the potential purchase behavior of Chinese consumers of new energy hybrid electric vehicles

The automotive industry has paid close attention to the promising future of new energy vehicles, and the new energy hybrid electric vehicles that fall under this category are gradually entering the public eye. This paper uses the SPSS software to conduct an experimental study on the “purchase preference for new energy hybrid vehicles” and its influencing factors of different types of consumers in China, based on 379 questionnaires and the results of situational experiments conducted by the research group in 24 cities across the country. The findings are as follows: 1) Different categories of consumers have a large gap in their cognitive preferences for new energy hybrid electric vehicles; 2) There is little difference in “purchase preference for new energy hybrid electric vehicles” among different categories of consumers; 3) The improvement of education and income has a significant effect on promoting consumers’ “environmental awareness”; 4) Consumers’ perception of the government’s new energization policy is positive. Based on the preceding conclusions, this paper puts forward the policy recommendations to promote new energy hybrid electric vehicles.
Challenges and opportunities in analyzing and modeling peptide presentation by HLA-II proteins

The human leukocyte antigen (HLA) proteins are an indispensable component of adaptive immunity because of their role in presenting self and foreign peptides to T cells. Further, many complex diseases are associated with genetic variation in the HLA region, implying an important role for specific HLA-presented peptides in the etiology of these diseases. Identifying the specific set of peptides presented by an individual’s HLA proteins in vivo, as a whole being referred to as the immunopeptidome, has therefore gathered increasing attention for different reasons. For example, identifying neoepitopes for cancer immunotherapy, vaccine development against infectious pathogens, or elucidating the role of HLA in autoimmunity. Despite the tremendous progress made during the last decade in these areas, several questions remain unanswered. In this perspective, we highlight five remaining key challenges in the analysis of peptide presentation and T cell immunogenicity and discuss potential solutions to these problems. We believe that addressing these questions would not only improve our understanding of disease etiology but will also have a direct translational impact in terms of engineering better vaccines and in developing more potent immunotherapies.
Occupational exposure in swine farm defines human skin and nasal microbiota

Anthropogenic environments take an active part in shaping the human microbiome. Herein, we studied skin and nasal microbiota dynamics in response to the exposure in confined and controlled swine farms to decipher the impact of occupational exposure on microbiome formation. The microbiota of volunteers was longitudinally profiled in a 9-months survey, in which the volunteers underwent occupational exposure during 3-month internships in swine farms. By high-throughput sequencing, we showed that occupational exposure compositionally and functionally reshaped the volunteers’ skin and nasal microbiota. The exposure in farm A reduced the microbial diversity of skin and nasal microbiota, whereas the microbiota of skin and nose increased after exposure in farm B. The exposure in different farms resulted in compositionally different microbial patterns, as the abundance of Actinobacteria sharply increased at expense of Firmicutes after exposure in farm A, yet Proteobacteria became the most predominant in the volunteers in farm B. The remodeled microbiota composition due to exposure in farm A appeared to stall and persist, whereas the microbiota of volunteers in farm B showed better resilience to revert to the pre-exposure state within 9 months after the exposure. Several metabolic pathways, for example, the styrene, aminobenzoate, and N-glycan biosynthesis, were significantly altered through our PICRUSt analysis, and notably, the function of beta-lactam resistance was predicted to enrich after exposure in farm A yet decrease in farm B. We proposed that the differently modified microbiota patterns might be coordinated by microbial and non-microbial factors in different swine farms, which were always environment-specific. This study highlights the active role of occupational exposure in defining the skin and nasal microbiota and sheds light on the dynamics of microbial patterns in response to environmental conversion.
Single-cell RNA sequencing depicts metabolic changes in children with aplastic anemia

Introduction Aplastic anemia (AA) is a bone marrow hematopoietic failure syndrome mediated by immune cells. The mechanism of this immune disorder is not well understood and therapeutic strategies still need to be improved. Methods Studies have found that abnormalities in metabolisms promote the survival of AA cells. In recent years, an increasing number of studies have reported the immunosuppressive therapy for the treatment of AA. In this study, we analyzed the transcriptome of AA from peripheral blood compared with healthy donors by single-cell sequencing and identified the affected metabolic pathways including lysine degradation. We demonstrated that the metabolic abnormalities of T lymphocytes mainly focus on glycolysis/gluconeogenesis. In addition, the metabolic abnormalities of natural killer cells concentrated in oxidative phosphorylation. Results The key genes involved in abnormal metabolic processes were Neustein neurotrophic factor (NENF), inositol polyphosphate-4-phosphatase type II B (INPP4B), aldo-keto reductase family 1, member C3 (AKR1C3), and carbohydrate (N-acetylglucosamine-6-O) sulfotransferase 2 (CHST2) by differential gene expression analysis. Discussion Molecule interaction analysis showed that tumor necrosis factor superfamily, member 12 (TNFSM12) in tumor necrosis factor (TNF) signaling was broadly activated in AA. In conclusion, we suppose that the treatment of the immune cells’ abnormal metabolic pathway may contribute to the development of novel strategies to treat AA.
The diagnostic efficacy and inappropriate biopsy rate of ACR TI-RADS and ATA guidelines for thyroid nodules in children and adolescents

Background This study is aimed at evaluating the diagnostic efficacy and unnecessary fine-needle aspiration (FNA) rate of ultrasound-based risk stratification for thyroid nodules in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) risk stratification systems. Methods Children and adolescents with pathology confirmed thyroid nodules were retrospectively included in this study. A total of 217 thyroid nodules from multicenter of Union Medical College Hospital, China Japan Friendship Hospital and Civil Aviation Hospital were included, the diagnostic efficiency and unnecessary FNA rate were calculated according to ACR and ATA guidelines. Results Among all thyroid nodules, 139 nodules were malignant, and 78 nodules were benign. Choosing ATA high suspicion and ACR TI-RADS TR5 as benign and malignant cut-off points, the area under the curve and sensitivity of ATA were higher than ACR (AUC: 0.887 vs 0.840, p=0.0037; sensitivity 81.3% vs 71.0%, P <0.049;specificity 96.2% vs 97.4%, p=1.000;specificity both 85.9%); choosing high/intermediate suspicion in ATA and ACR TR4/5 as benign and malignant cut-off points, the two guidelines demonstrated similar diagnostic efficacy (AUC:0.890 vs 0.897, p=0.6038, sensitivity 92.1% vs 93.5%, P =0.817;specificity both 85.9%, p=1.000). The inappropriate FNA rate of ACR guideline was relatively lower (ATA 42.9% vs ACR 27.2%, P <0.001). If ACR TI-RADS TR5 nodules less than 1.0cm were included in the FNA indication, the unnecessary biopsy rate would be further reduced to 17.9%. Conclusion This study indicated that both ATA and ACR TI-RADS risk stratification systems could provide a feasible differential diagnosis of benign and malignant thyroid nodules, while the ACR risk stratification system demonstrates a lower rate of inappropriate FNA rate. In addition, it was necessary to further study the minimum FNA threshold of thyroid nodules in Children and adolescents in order to reduce the missed biopsy rate of malignant nodules.
New technique for the treatment of fresh bony mallet finger: A retrospective case series study

Background The bony mallet finger is a tear fracture of the extensor tendon, resulting in a flexion deformity of the finger, which affects both the function of the finger. The classical Ishiguro's method is associated with damage to the cartilage of the distal interphalangeal (DIP) joint and always lead to the joint stiffness. This paper explores a new technique to overcome the shortcomings of the classical Ishiguro's method and achieve better clinical efficacy. Methods We examined 15 patients with bony mallet fingers, 9 males and 6 females, from February 2020 to June 2022, ranged from 23 to 58 years, including 1 case of index finger, 5 cases of middle finger, 3 cases of ring finger and 6 cases of little finger. The median course of the injury to surgery was 2 days (range, 1∼7 days). All had fresh closed injuries, according to the Wehbe and Schneider classification: 4 cases of type IA, 6 cases of type IB, 3 cases of type IIA and 2 cases of type IIB. All patients were treated surgically by the new technique. Post-operative follow-up was conducted to record the healing of the fracture, the pain of the affected finger and the function of joint movement. Results The 15 cases were followed up after surgery. The median active range of motion was 65° (range, 55∼75°). The median extension deficit of DIP joint was 0° (range, 0∼11°). The median clinical healing time of the fracture was 6 weeks (range, 6∼10 weeks). None of the patients experienced significant pain. The patients were assessed according to the Crawford criteria at the final follow-up: 11 cases were assessed as excellent, 3 cases were assessed as good and 1 case was assessed as fair. No loss of fracture repositioning, loosening of internal fixation, skin necrosis or infection was observed. Conclusion The application of the new technique for the treatment of bony mallet fingers has the advantages of good stability, fracture healing and functional recovery of the DIP joint, making it an ideal surgical procedure for the treatment of fresh bony mallet fingers.