KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning

Kinship verification is an emerging task in computer vision with multiple potential applications. However, there's no large enough kinship dataset to train a representative and robust model, which is a limitation for achieving better performance. Moreover, face verification is known to exhibit bias, which has not been dealt with by previous kinship verification works and sometimes even results in serious issues. So we first combine existing kinship datasets and label each identity with the correct race in order to take race information into consideration and provide a larger and complete dataset, called KinRace dataset. Secondly, we propose a multi-task learning model structure with attention module to enhance accuracy, which surpasses state-of-the-art performance. Lastly, our fairness-aware contrastive loss function with adversarial learning greatly mitigates racial bias. We introduce a debias term into traditional contrastive loss and implement gradient reverse in race classification task, which is an innovative idea to mix two fairness methods to alleviate bias. Exhaustive experimental evaluation demonstrates the effectiveness and superior performance of the proposed KFC in both standard deviation and accuracy at the same time.Comment: Accepted by BMVC 202

Environment Diversification with Multi-head Neural Network for Invariant Learning

Neural networks are often trained with empirical risk minimization; however, it has been shown that a shift between training and testing distributions can cause unpredictable performance degradation. On this issue, a research direction, invariant learning, has been proposed to extract invariant features insensitive to the distributional changes. This work proposes EDNIL, an invariant learning framework containing a multi-head neural network to absorb data biases. We show that this framework does not require prior knowledge about environments or strong assumptions about the pre-trained model. We also reveal that the proposed algorithm has theoretical connections to recent studies discussing properties of variant and invariant features. Finally, we demonstrate that models trained with EDNIL are empirically more robust against distributional shifts.Comment: In Proceedings of 36th Conference on Neural Information Processing Systems (NeurIPS 2022

Modeling Ligand-Receptor Interaction for Some MHC Class II HLA-DR4 Peptide Mimetic Inhibitors Using Several Molecular Docking and 3D QSAR Techniques

The ligand-receptor interaction between some peptidomimetic inhibitors and a class II MHC peptide presenting molecule, the HLA-DR4 receptor, was modeled using some three-dimensional (3D) quantitative structure-activity relationship (QSAR) methods such as the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and a pharmacophore building method, the Catalyst program. The structures of these peptidomimetic inhibitors were generated theoretically, and the conformations used in the 3D QSAR studies were defined by docking them into the known structure of HLA-DR4 receptor through the GOLD, GLIDE Rigidly, GLIDE Flexible, and Xscore programs. Some of the parameters used in these docking programs were selected by docking an X-ray ligand into the receptor and comparing the root-means-square difference (RMSD) computed between the coordinates of the X-ray and docked structure. However, the goodness of a docking result for docking a series of peptidomimetic inhibitors into the HLA-DR4 receptor was judged by comparing the Spearman's rank correlation coefficient computed between each docking result and the activity data taken from the literature. The best CoMFA and CoMSIA models were constructed using the aligned structures of the best docking result. The CoMSIA was conducted in a stepwise manner to identify some important molecular features that were further employed in a pharmacophore building process by the Catalyst program. It was found that most inhibitors of the training set were accurately predicted by the best pharmacophore model, the Hypo1 hypothesis constructed. The deviation or conflict found between the actual and predicted activities of some inhibitors of both the training and the test sets were also investigated by mapping the Hypo1 hypothesis onto the corresponding structures of the inhibitors

Airborne dispersion of droplets during coughing: a physical model of viral transmission

The Covid-19 pandemic has focused attention on airborne transmission of viruses. Using realistic air flow simulation, we model droplet dispersion from coughing and study the transmission risk related to SARS-CoV-2. Although most airborne droplets are 8-16 $\mu$m in diameter, the droplets with the highest transmission potential are, in fact, 32-40 $\mu$m. Use of face masks is therefore recommended for both personal and social protection. We found social distancing effective at reducing transmission potential across all droplet sizes. However, the presence of a human body 1 m away modifies the aerodynamics so that downstream droplet dispersion is enhanced, which has implications on safe distancing in queues. Based on median viral load, we found that an average of 0.55 viral copies is inhaled at 1 m distance per cough. Droplet evaporation results in significant reduction in droplet counts, but airborne transmission remains possible even under low humidity conditions

Biodistribution and pharmacokinetics of 188Re-liposomes and their comparative therapeutic efficacy with 5-fluorouracil in C26 colonic peritoneal carcinomatosis mice

Chia-Che Tsai1, Chih-Hsien Chang1, Liang-Cheng Chen1, Ya-Jen Chang1, Keng-Li Lan2, Yu-Hsien Wu1, Chin-Wei Hsu1, I-Hsiang Liu1, Chung-Li Ho1, Wan-Chi Lee1, Hsiao-Chiang Ni1, Tsui-Jung Chang1, Gann Ting3, Te-Wei Lee11Institute of Nuclear Energy Research, Taoyuan, 2Cancer Center, Taipei Veterans General Hospital, Taipei, 3National Health Research Institutes, Taipei, Taiwan, ROCBackground: Nanoliposomes are designed as carriers capable of packaging drugs through passive targeting tumor sites by enhanced permeability and retention (EPR) effects. In the present study the biodistribution, pharmacokinetics, micro single-photon emission computed tomography (micro-SPECT/CT) image, dosimetry, and therapeutic efficacy of 188Re-labeled nanoliposomes (188Re-liposomes) in a C26 colonic peritoneal carcinomatosis mouse model were evaluated.Methods: Colon carcinoma peritoneal metastatic BALB/c mice were intravenously administered 188Re-liposomes. Biodistribution and micro-SPECT/CT imaging were performed to determine the drug profile and targeting efficiency of 188Re-liposomes. Pharmacokinetics study was described by a noncompartmental model. The OLINDA|EXM® computer program was used for the dosimetry evaluation. For therapeutic efficacy, the survival, tumor, and ascites inhibition of mice after treatment with 188Re-liposomes and 5-fluorouracil (5-FU), respectively, were evaluated and compared.Results: In biodistribution, the highest uptake of 188Re-liposomes in tumor tissues (7.91% ± 2.02% of the injected dose per gram of tissue [%ID/g]) and a high tumor to muscle ratio (25.8 ± 6.1) were observed at 24 hours after intravenous administration. The pharmacokinetics of 188Re-liposomes showed high circulation time and high bioavailability (mean residence time [MRT] = 19.2 hours, area under the curve [AUC] = 820.4%ID/g*h). Micro-SPECT/CT imaging of 188Re-liposomes showed a high uptake and targeting in ascites, liver, spleen, and tumor. The results were correlated with images from autoradiography and biodistribution data. Dosimetry study revealed that the 188Re-liposomes did not cause high absorbed doses in normal tissue but did in small tumors. Radiotherapeutics with 188Re-liposomes provided better survival time (increased by 34.6% of life span; P < 0.05), tumor and ascites inhibition (decreased by 63.4% and 83.3% at 7 days after treatment; P < 0.05) in mice compared with chemotherapeutics of 5-fluorouracil (5-FU).Conclusion: The use of 188Re-liposomes for passively targeted tumor therapy had greater therapeutic effect than the currently clinically applied chemotherapeutics drug 5-FU in a colonic peritoneal carcinomatosis mouse model. This result suggests that 188Re-liposomes have potential benefit and are safe in treating peritoneal carcinomatasis of colon cancer.Keywords: biodistribution, dosimetry, 5-fluorouracil, micro-SPECT/CT, 188Re-liposome

A gelatin/collagen/polycaprolactone scaffold for skin regeneration

Background A tissue-engineered skin substitute, based on gelatin (“G”), collagen (“C”), and poly(ε-caprolactone) (PCL; “P”), was developed. Method G/C/P biocomposites were fabricated by impregnation of lyophilized gelatin/collagen (GC) mats with PCL solutions, followed by solvent evaporation. Two different GC:PCL ratios (1:8 and 1:20) were used. Results Differential scanning calorimetry revealed that all G/C/P biocomposites had characteristic melting point of PCL at around 60 °C. Scanning electron microscopy showed that all biocomposites had similar fibrous structures. Good cytocompatibility was present in all G/C/P biocomposites when incubated with primary human epidermal keratinocytes (PHEK), human dermal fibroblasts (PHDF) and human adipose-derived stem cells (ASCs) in vitro. All G/C/P biocomposites exhibited similar cell growth and mechanical characteristics in comparison with C/P biocomposites. G/C/P biocomposites with a lower collagen content showed better cell proliferation than those with a higher collagen content in vitro. Due to reasonable mechanical strength and biocompatibility in vitro, G/C/P with a lower content of collagen and a higher content of PCL (GCLPH) was selected for animal wound healing studies. According to our data, a significant promotion in wound healing and skin regeneration could be observed in GCLPH seeded with adipose-derived stem cells by Gomori’s trichrome staining. Conclusion This study may provide an effective and low-cost wound dressings to assist skin regeneration for clinical use

Testing the viability of the interacting holographic dark energy model by using combined observational constraints

Using the data coming from the new 182 Gold type Ia supernova samples, the shift parameter of the Cosmic Microwave Background given by the three-year Wilkinson Microwave Anisotropy Probe observations, and the baryon acoustic oscillation measurement from the Sloan Digital Sky Survey, $H(z)$ and lookback time measurements, we have performed a statistical joint analysis of the interacting holographic dark energy model. Consistent parameter estimations show us that the interacting holographic dark energy model is a viable candidate to explain the observed acceleration of our universe.Comment: 15 pages, 9 figures, accepted for publication in JCA