Immigration documentation statuses evoke racialized faceism in mental representations.

U.S. immigration discourse has spurred interest in characterizing who illegalized immigrants are or perceived to be. What are the associated visual representations of migrant illegality? Across two studies with undergraduate and online samples (N = 686), we used face-based reverse correlation and similarity sorting to capture and compare mental representations of illegalized immigrants, native-born U.S. citizens, and documented immigrants. Documentation statuses evoked racialized imagery. Immigrant representations were dark-skinned and perceived as non-white, while citizen representations were light-skinned, evaluated positively, and perceived as white. Legality further differentiated immigrant representations: documentation conjured trustworthy representations, illegality conjured threatening representations. Participants spontaneously sorted unlabeled faces by documentation status in a spatial arrangement task. Faces' spatial similarity correlated with their similarity in pixel luminance and "American" ratings, confirming racialized distinctions. Representations of illegalized immigrants were uniquely racialized as dark-skinned un-American threats, reflecting how U.S. imperialism and colorism set conditions of possibility for existing representations of migrant illegalization.

Craniofacial identification standards: A review of reliability, reproducibility, and implementation.

There are numerous anatomical and anthropometrical standards that can be utilised for craniofacial analysis and identification. These standards originate from a wide variety of sources, such as orthodontic, maxillofacial, surgical, anatomical, anthropological and forensic literature, and numerous media have been employed to collect data from living and deceased subjects. With the development of clinical imaging and the enhanced technology associated with this field, multiple methods of data collection have become accessible, including Computed Tomography, Cone-Beam Computed Tomography, Magnetic Resonance Imaging, Radiographs, Three-dimensional Scanning, Photogrammetry and Ultrasound, alongside the more traditional in vivo methods, such as palpation and direct measurement, and cadaveric human dissection. Practitioners often struggle to identify the most appropriate standards and research results are frequently inconsistent adding to the confusion. This paper aims to clarify how practitioners can choose optimal standards, which standards are the most reliable and when to apply these standards for craniofacial identification. This paper describes the advantages and disadvantages of each mode of data collection and collates published research to review standards across different populations for each facial feature. This paper does not aim to be a practical instruction paper; since this field encompasses a wide range of 2D and 3D approaches (e.g., clay sculpture, sketch, automated, computer-modelling), the implementation of these standards is left to the individual practitioner.

Auditory neuroscience: Sounds make the face move.

Animals including humans often react to sounds by involuntarily moving their face and body. A new study shows that facial movements provide a simple and reliable readout of a mouse's hearing ability that is more sensitive than traditional measurements.

The Multimodal Trust Effects of Face, Voice, and Sentence Content.

Trust is an aspect critical to human social interaction and research has identified many cues that help in the assimilation of this social trait. Two of these cues are the pitch of the voice and the width-to-height ratio of the face (fWHR). Additionally, research has indicated that the content of a spoken sentence itself has an effect on trustworthiness; a finding that has not yet been brought into multisensory research. The current research aims to investigate previously developed theories on trust in relation to vocal pitch, fWHR, and sentence content in a multimodal setting. Twenty-six female participants were asked to judge the trustworthiness of a voice speaking a neutral or romantic sentence while seeing a face. The average pitch of the voice and the fWHR were varied systematically. Results indicate that the content of the spoken message was an important predictor of trustworthiness extending into multimodality. Further, the mean pitch of the voice and fWHR of the face appeared to be useful indicators in a multimodal setting. These effects interacted with one another across modalities. The data demonstrate that trust in the voice is shaped by task-irrelevant visual stimuli. Future research is encouraged to clarify whether these findings remain consistent across genders, age groups, and languages.

Relationship between bite force, occlusal contact area, and three-dimensional facial soft tissue in dentofacial deformities.

PURPOSE: This study aimed to investigate three-dimensional facial soft tissue dimensions, maximum bite force (MBF), and occlusal contact area in patients with DFD. In addition, we analyzed the relationship between MBF and the three-dimensional facial measurements. METHODS: Thirty-two patients with skeletal Class III DFD and 20 patients with Class II DFD underwent a soft tissue evaluation using surface laser scanning, as well as MBF and occlusal contact area assessments. The DFD groups were compared with each other and with 25 healthy subjects. RESULTS: Significant morphological differences were found in the transversal, vertical, and anteroposterior dimensions between Class II DFD and Class III DFD. Both DFD groups presented an increased linear distance of chin height, which was strongly related with decreased MBF magnitude. The DFD groups exhibited lower MBF and occlusal contact area, with no significant differences between Class II and Class III DFD. CONCLUSION: The presence of DFD affected 3D measurements of facial soft tissue, causing variations beyond normal limits, lower MBF, and occlusal contact area in both Class II and Class III DFD patients. The vertical dimension might have influenced the lower MBF magnitude in the studied skeletal deformities.

The resolution of face perception varies systematically across the visual field.

Visual abilities tend to vary predictably across the visual field-for simple low-level stimuli, visibility is better along the horizontal vs. vertical meridian and in the lower vs. upper visual field. In contrast, face perception abilities have been reported to show either distinct or entirely idiosyncratic patterns of variation in peripheral vision, suggesting a dissociation between the spatial properties of low- and higher-level vision. To assess this link more clearly, we extended methods used in low-level vision to develop an acuity test for face perception, measuring the smallest size at which facial gender can be reliably judged in peripheral vision. In 3 experiments, we show the characteristic inversion effect, with better acuity for upright faces than inverted, demonstrating the engagement of high-level face-selective processes in peripheral vision. We also observe a clear advantage for gender acuity on the horizontal vs. vertical meridian and a smaller-but-consistent lower- vs. upper-field advantage. These visual field variations match those of low-level vision, indicating that higher-level face processing abilities either inherit or actively maintain the characteristic patterns of spatial selectivity found in early vision. The commonality of these spatial variations throughout the visual hierarchy means that the location of faces in our visual field systematically influences our perception of them.

Causal relationship between dyslipidemia and risk of facial aging: Insights from Mendelian randomization in East Asian populations.

BACKGROUND: Emerging observational studies showed an association between dyslipidemia and aging. However, it remains unclear whether this association is causal, particularly in the case of Asians, which are aging more rapidly than other continents. Given the visible manifestations of aging often include changes in facial appearance, the objective of this study is to assess the causal relationship between dyslipidemia and facial aging in East Asian populations. METHODS: SNPs related to dyslipidemia in East Asian people such as Total cholesterol (TC), High-density-lipoprotein cholesterol (HDL), Low-density-lipoprotein cholesterol (LDL), and Triglyceride (TG) along with outcomes data on facial aging, were extracted from public genome-wide association studies (GWAS). A two-sample Mendelian randomization (MR) analysis was then performed using publicly available GWAS data to investigate the potential causal relationship. The effect estimates were primarily calculated using the fixed-effects inverse variance weighted (IVW) method. RESULTS: Totally, 88 SNPs related to HDL among 70657 East Asian participants in GWAS. Based on the primary causal effects model using MR analyses with the IVW method, high HDL level was demonstrated as significantly related to the risk of facial aging (OR, 1.060; 95% CI, 1.005-1.119, p = 0.034), while high TC level (OR, 0.995; 95% CI, 0.920-1.076, p = 0.903), high LDL level (OR, 0.980, 95% CI, 0.924-1.041, p = 0.515), as well as high TG level (OR, 0.999, 95% CI, 0.932-1.071, p = 0.974), showed no significant correlation with facial aging. CONCLUSIONS: The two-sample MR analysis conducted in this study revealed a positive causal relationship between high HDL levels and facial aging. In contrast, facial aging demonstrated no significant correlation with high levels of TC, LDL, or TG. Further large-sample prospective studies are needed to validate these findings and to provide appropriate recommendations regarding nutrition management to delay the aging process among old patients in East Asia.

The relevance and accuracy of an AI algorithm-based descriptor on 23 facial attributes in a diverse female US population.

BACKGROUND: The response of AI in situations that mimic real life scenarios is poorly explored in populations of high diversity. OBJECTIVE: To assess the accuracy and validate the relevance of an automated, algorithm-based analysis geared toward facial attributes devoted to the adornment routines of women. METHODS: In a cross-sectional study, two diversified groups presenting similar distributions such as age, ancestry, skin phototype, and geographical location was created from the selfie images of 1041 female in a US population. 521 images were analyzed as part of a new training dataset aimed to improve the original algorithm and 520 were aimed to validate the performance of the AI. From a total 23 facial attributes (16 continuous and 7 categorical), all images were analyzed by 24 make-up experts and by the automated descriptor tool. RESULTS: For all facial attributes, the new and the original automated tool both surpassed the grading of the experts on a diverse population of women. For the 16 continuous attributes, the gradings obtained by the new system strongly correlated with the assessment made by make-up experts (r ≥ 0.80; p < 0.0001) and supported by a low error rate. For the seven categorical attributes, the overall accuracy of the AI-facial descriptor was improved via enrichment of the training dataset. However, some weaker performance in spotting specific facial attributes were noted. CONCLUSION: In conclusion, the AI-automatic facial descriptor tool was deemed accurate for analysis of facial attributes for diverse women although some skin complexion, eye color, and hair features required some further finetuning.

A Practical Algorithm for Integrating Skincare to Improve Patient Outcomes and Satisfaction With Energy-Based Dermatologic Procedures.

BACKGROUND: Medical aesthetic procedures for facial antiaging with laser and energy-based devices (EBDs) are rapidly increasing, but standards integrating skincare before, during, and after these treatments are lacking. The algorithm for integrated skin care for facial antiaging treatment with EBDs aims to stimulate healing, reduce downtime, and improve comfort and treatment outcomes. METHODS: A panel of 8 global physicians employed a modified Delphi method and reached a consensus on the algorithm integrating skincare based on the best available evidence, the panel's clinical experience, and opinions. RESULTS: The algorithm has a pretreatment (starts 2 - 4 weeks before the procedure) and treatment (day of treatment) section, followed by care after the procedure (0 - 7 days) and follow-up care (1 - 4 weeks after the procedure or ongoing). Applying a broad-spectrum sunscreen with an SPF 50 or higher, combined with protective measures such as wearing a wide-brimmed hat and sunglasses, is recommended to protect the face from sun exposure. Dyschromia is a significant concern for those with skin of color (SOC). Clinicians may recommend skincare using a gentle cleanser and moisturizer containing vitamins C and E, retinoid, or other ingredients such as niacinamide, kojic acid, licorice root extract, azelaic acid, and tranexamic acid, depending on the patient's facial skin condition. CONCLUSION: Medical aesthetic procedures for facial antiaging with EBDs integrating skincare or topical treatments may improve outcomes and patient satisfaction. Topical antioxidants and free radical quenchers can combat photodamage and may offer a safe alternative to topical hydroquinone.  J Drugs Dermatol. 2024;23(5):353-359.     doi:10.36849/JDD.8092.

Contrasting neurofunctional correlates of face- and visuospatial-processing in children and adolescents with Williams syndrome: convergent results from four fMRI paradigms.

Understanding neurogenetic mechanisms underlying neuropsychiatric disorders such as schizophrenia and autism is complicated by their inherent clinical and genetic heterogeneity. Williams syndrome (WS), a rare neurodevelopmental condition in which both the genetic alteration (hemideletion of ~ twenty-six 7q11.23 genes) and the cognitive/behavioral profile are well-defined, offers an invaluable opportunity to delineate gene-brain-behavior relationships. People with WS are characterized by increased social drive, including particular interest in faces, together with hallmark difficulty in visuospatial processing. Prior work, primarily in adults with WS, has searched for neural correlates of these characteristics, with reports of altered fusiform gyrus function while viewing socioemotional stimuli such as faces, along with hypoactivation of the intraparietal sulcus during visuospatial processing. Here, we investigated neural function in children and adolescents with WS by using four separate fMRI paradigms, two that probe each of these two cognitive/behavioral domains. During the two visuospatial tasks, but not during the two face processing tasks, we found bilateral intraparietal sulcus hypoactivation in WS. In contrast, during both face processing tasks, but not during the visuospatial tasks, we found fusiform hyperactivation. These data not only demonstrate that previous findings in adults with WS are also present in childhood and adolescence, but also provide a clear example that genetic mechanisms can bias neural circuit function, thereby affecting behavioral traits.

A behavioral advantage for the face pareidolia illusion in peripheral vision.

Investigation of visual illusions helps us understand how we process visual information. For example, face pareidolia, the misperception of illusory faces in objects, could be used to understand how we process real faces. However, it remains unclear whether this illusion emerges from errors in face detection or from slower, cognitive processes. Here, our logic is straightforward; if examples of face pareidolia activate the mechanisms that rapidly detect faces in visual environments, then participants will look at objects more quickly when the objects also contain illusory faces. To test this hypothesis, we sampled continuous eye movements during a fast saccadic choice task-participants were required to select either faces or food items. During this task, pairs of stimuli were positioned close to the initial fixation point or further away, in the periphery. As expected, the participants were faster to look at face targets than food targets. Importantly, we also discovered an advantage for food items with illusory faces but, this advantage was limited to the peripheral condition. These findings are among the first to demonstrate that the face pareidolia illusion persists in the periphery and, thus, it is likely to be a consequence of erroneous face detection.

Aesthetic perception of patient in developmental age in interceptive orthodontic treatment.

AIM: Patients at development age show considerable attention to the shape of the face from both an aesthetic and relational point of view, to arouse interest from researchers. There are few studies related to profile analysis in patients of developmental age. Therefore, the objective of the present study was to analyse the importance of the aesthetic perception of the patient in development age in relation to the profile, before and after interceptive orthodontic treatment. MATERIALS: A sample of 25 patients who came to our observation for dentoskeletal malocclusions was considered. A questionnaire was proposed to each patient, before and after the interceptive orthodontic treatment (T0 and T1), to evaluate the aesthetic perception before and after the orthodontic treatment and its psychosocial impact. Profile analysis was performed using photographic documentation (at T0 and T1). The variables considered were the Ricketts line, the facial convexity angle, the nasolabial angle, and the labiomental angle. CONCLUSION: Interceptive orthodontic treatment has proven to be of valid clinical and psychological help. This result is confirmed by the complete aesthetic satisfaction of the patient in the frontal and latero-lateral planes.

Electroencephalogram-Based Facial Gesture Recognition Using Self-Organizing Map.

Brain-computer interfaces (BCIs) allow information to be transmitted directly from the human brain to a computer, enhancing the ability of human brain activity to interact with the environment. In particular, BCI-based control systems are highly desirable because they can control equipment used by people with disabilities, such as wheelchairs and prosthetic legs. BCIs make use of electroencephalograms (EEGs) to decode the human brain's status. This paper presents an EEG-based facial gesture recognition method based on a self-organizing map (SOM). The proposed facial gesture recognition uses α, ß, and θ power bands of the EEG signals as the features of the gesture. The SOM-Hebb classifier is utilized to classify the feature vectors. We utilized the proposed method to develop an online facial gesture recognition system. The facial gestures were defined by combining facial movements that are easy to detect in EEG signals. The recognition accuracy of the system was examined through experiments. The recognition accuracy of the system ranged from 76.90% to 97.57% depending on the number of gestures recognized. The lowest accuracy (76.90%) occurred when recognizing seven gestures, though this is still quite accurate when compared to other EEG-based recognition systems. The implemented online recognition system was developed using MATLAB, and the system took 5.7 s to complete the recognition flow.

Enhancing Resilience in Biometric Research: Generation of 3D Synthetic Face Data Using Advanced 3D Character Creation Techniques from High-Fidelity Video Games and Animation.

Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines' capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed.

Intra-Individual Paired Mass Spectrometry Dataset for Decoding Solar-Induced Proteomic Changes in Facial Skin.

Photoaging is the premature aging of the skin caused by prolonged exposure to solar radiation. The visual alterations manifest as wrinkles, reduced skin elasticity, uneven skin tone, as well as other signs that surpass the expected outcomes of natural aging. Beyond these surface changes, there is a complex interplay of molecular alterations, encompassing shifts in cellular function, DNA damage, and protein composition disruptions. This data descriptor introduces a unique dataset derived from ten individuals, each with a minimum of 18 years of professional experience as a driver, who are asymmetrically and chronically exposed to solar radiation due to their driving orientation. Skin samples were independently collected from each side of the face using a microdermabrasion-like procedure and analyzed on an Exploris 240 mass spectrometer. Our adapted proteomic statistical framework leverages the sample pairing to provide robust insights. This dataset delves into the molecular differences in exposed skin and serves as a foundational resource for interdisciplinary research in photodermatology, targeted skincare treatments, and computational modelling of skin health.

Automated reconstruction: Predictive models based on facial morphology matrices.

Forensic Facial Approximation (FFA) has evolved, with techniques advancing to refine the intercorrelation between the soft-tissue facial profile and the underlying skull. FFA has become essential for identifying unknown persons in South Africa, where the high number of migrant and illegal labourers and many unidentified remains make the identification process challenging. However, existing FFA methods are based on American or European standards, rendering them inapplicable in a South African context. We addressed this issue by conducting a study to create prediction models based on the relationships between facial morphology and known factors, such as population affinity, sex, and age, in white South African and French samples. We retrospectively collected 184 adult cone beam computed tomography (CBCT) scans representing 76 white South Africans (29 males and 47 females) and 108 French nationals (54 males and 54 females) to develop predictive statistical models using a projection onto latent structures regression algorithm (PLSR). On training and untrained datasets, the accuracy of the estimated soft-tissue shape of the ears, eyes, nose, and mouth was measured using metric deviations. The predictive models were optimized by integrating additional variables such as sex and age. Based on trained data, the prediction errors for the ears, eyes, nose, and mouth ranged between 1.6 mm and 4.1 mm for white South Africans; for the French group, they ranged between 1.9 mm and 4.2 mm. Prediction errors on non-trained data ranged between 1.6 mm and 4.3 mm for white South Africans, whereas prediction errors ranging between 1.8 mm and 4.3 mm were observed for the French. Ultimately, our study provided promising predictive models. Although the statistical models can be improved, the inherent variability among individuals restricts the accuracy of FFA. The predictive validity of the models was improved by including sex and age variables and considering population affinity. By integrating these factors, more customized and accurate predictive models can be developed, ultimately strengthening the effectiveness of forensic analysis in the South African region.

Electrical stimulation of the lower eyelid orbicularis oculi muscle improves periocular dark circles.

BACKGROUND: We developed and tested the safety and efficacy of a cosmetic device to improve dark circles using electrical muscle stimulation of the orbicularis oculi muscle. METHODS: Overall, 18 participants (36 eyes) were studied. The following five items were evaluated before and after the intervention:(1) the Clinical Dark Circle Score using clinical findings and photographs, (2) transcutaneous oxygen partial pressure (TcPO2) on the lower eyelid, (3) thermography, (4) two-dimensional laser blood flowmetry, and (5) spectrophotometry. RESULTS: The mean score at baseline was 2.0 ± 0.90 (mean ± standard deviation), and that at the end of the study was 1.2 ± 1.0 (Wilcoxon signed-rank sum test, p < 0.0001), indicating a significant reduction. The spectrophotometer showed a significant decrease in a* and L* values before and after use (Wilcoxon signed-rank sum test, p < 0.0001). There was also a weak negative correlation between the change in score and the change in blood flow and TcPO2 measured using a laser perfusion device (Spearman's rank correlation coefficient, r = -0.32 and -0.39, respectively). Stratified analysis of the baseline score showed a strong negative correlation between the change in score and the change in spectrophotometric a* in the subjects/group with mild periocular dark circles (Spearman's rank correlation coefficient, r = -0.46). Contrastingly, no correlation was observed for any of the measurements in the subjects/group with severe periocular dark circles. After 1 month, no device-related ophthalmic adverse events were observed in any of the participants. CONCLUSION: Electrical muscle stimulation could improve periocular dark circles, especially in the subjects/group with mild periocular dark circles, and was safe.

Application of Stereo Digital Image Correlation on Facial Expressions Sensing.

Facial expression is an important way to reflect human emotions and it represents a dynamic deformation process. Analyzing facial movements is an effective means of understanding expressions. However, there is currently a lack of methods capable of analyzing the dynamic details of full-field deformation in expressions. In this paper, in order to enable effective dynamic analysis of expressions, a classic optical measuring method called stereo digital image correlation (stereo-DIC or 3D-DIC) is employed to analyze the deformation fields of facial expressions. The forming processes of six basic facial expressions of certain experimental subjects are analyzed through the displacement and strain fields calculated by 3D-DIC. The displacement fields of each expression exhibit strong consistency with the action units (AUs) defined by the classical Facial Action Coding System (FACS). Moreover, it is shown that the gradient of the displacement, i.e., the strain fields, offers special advantages in characterizing facial expressions due to their localized nature, effectively sensing the nuanced dynamics of facial movements. By processing extensive data, this study demonstrates two featured regions in six basic expressions, one where deformation begins and the other where deformation is most severe. Based on these two regions, the temporal evolutions of the six basic expressions are discussed. The presented investigations demonstrate the superior performance of 3D-DIC in the quantitative analysis of facial expressions. The proposed analytical strategy might have potential value in objectively characterizing human expressions based on quantitative measurement.

Emotion Classification Based on Pulsatile Images Extracted from Short Facial Videos via Deep Learning.

Most human emotion recognition methods largely depend on classifying stereotypical facial expressions that represent emotions. However, such facial expressions do not necessarily correspond to actual emotional states and may correspond to communicative intentions. In other cases, emotions are hidden, cannot be expressed, or may have lower arousal manifested by less pronounced facial expressions, as may occur during passive video viewing. This study improves an emotion classification approach developed in a previous study, which classifies emotions remotely without relying on stereotypical facial expressions or contact-based methods, using short facial video data. In this approach, we desire to remotely sense transdermal cardiovascular spatiotemporal facial patterns associated with different emotional states and analyze this data via machine learning. In this paper, we propose several improvements, which include a better remote heart rate estimation via a preliminary skin segmentation, improvement of the heartbeat peaks and troughs detection process, and obtaining a better emotion classification accuracy by employing an appropriate deep learning classifier using an RGB camera input only with data. We used the dataset obtained in the previous study, which contains facial videos of 110 participants who passively viewed 150 short videos that elicited the following five emotion types: amusement, disgust, fear, sexual arousal, and no emotion, while three cameras with different wavelength sensitivities (visible spectrum, near-infrared, and longwave infrared) recorded them simultaneously. From the short facial videos, we extracted unique high-resolution spatiotemporal, physiologically affected features and examined them as input features with different deep-learning approaches. An EfficientNet-B0 model type was able to classify participants' emotional states with an overall average accuracy of 47.36% using a single input spatiotemporal feature map obtained from a regular RGB camera.

A Clinical, Pharmacological, and Formulation Evaluation of Melatonin in the Treatment of Ocular Disorders-A Systematic Review.

Melatonin's cytoprotective properties may have therapeutic implications in treating ocular diseases like glaucoma and age-related macular degeneration. Literature data suggest that melatonin could potentially protect ocular tissues by decreasing the production of free radicals and pro-inflammatory mediators. This study aims to summarize the screened articles on melatonin's clinical, pharmacological, and formulation evaluation in treating ocular disorders. The identification of relevant studies on the topic in focus was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. The studies were searched in the following databases and web search engines: Pubmed, Scopus, Science Direct, Web of Science, Reaxys, Google Scholar, Google Patents, Espacenet, and Patentscope. The search time interval was 2013-2023, with the following keywords: melatonin AND ocular OR ophthalmic AND formulation OR insert AND disease. Our key conclusion was that using melatonin-loaded nano-delivery systems enabled the improved permeation of the molecule into intraocular tissues and assured controlled release profiles. Although preclinical studies have demonstrated the efficacy of developed formulations, a considerable gap has been observed in the clinical translation of the results. To overcome this failure, revising the preclinical experimental phase might be useful by selecting endpoints close to clinical ones.