Considering the Role of Human Empathy in AI-Driven Therapy

Recent breakthroughs in artificial intelligence (AI) language models have elevated the vision of using conversational AI support for mental health, with a growing body of literature indicating varying degrees of efficacy. In this paper, we ask when, in therapy, it will be easier to replace humans and, conversely, in what instances, human connection will still be more valued. We suggest that empathy lies at the heart of the answer to this question. First, we define different aspects of empathy and outline the potential empathic capabilities of humans versus AI. Next, we consider what determines when these aspects are needed most in therapy, both from the perspective of therapeutic methodology and from the perspective of patient objectives. Ultimately, our goal is to prompt further investigation and dialogue, urging both practitioners and scholars engaged in AI-mediated therapy to keep these questions and considerations in mind when investigating AI implementation in mental health

Thymosin beta4 sequesters actin in cystic fibrosis sputum and decreases sputum cohesivity in vitro

Filamentous actin (F-actin) forms polymers that contribute to the abnormal biophysical properties of sputum. Thymosin beta4 (Tbeta4) is the major monomeric actin-sequestering peptide in cells and can depolymerize F-actin. Tbeta4 could potentially decrease sputum viscoelasticity and adhesivity and improve sputum clearance. Sputum was collected during pulmonary function testing from 17 subjects during a cystic fibrosis (CF) center visit. Sputum rheology, cough and ciliary transportability, and interfacial tension were measured before and after the addition of dornase alfa at 30 microg/mL; Tbeta4 at 0.3, 3, 30, and 150 microg/mL; and Tbeta4 with dornase alfa at 1.5 microg/mL each. Sputum was separately incubated with Tbeta4 at 30 microg/mL for 0, 10, 20, or 60 min. There was a direct relationship between actin filament length and sputum cohesivity. There was a dose-dependent threshold decrease in cohesivity with Tbeta4 and a time-dependent decrease in cohesivity over 60 min at 30 microg/mL. With the combination of dornase alfa and Tbeta4 at 1.5 microg/mL each, there was a 70% decrease in G*s and a 65% decrease in G' at 1 rad/s (p = 0.013). There was a 44% increase in cough transportability of sputum in vitro (p = 0.037) and a 71% increase in mucociliary transportability of sputum in vitro (p = 0.013) relative to control with the combination of dornase alfa and Tbeta4, but no significant change with dornase alfa or Tbeta4 alone at any concentration. Actin polymer filament length is correlated with sputum cohesivity. Tbeta4 depolymerizes CF sputum actin in both a dose-dependent and a time-dependent manner. An apparent synergy of Tbeta4 on actin and dornase on DNA may be explained by the combined effect of actin depolymerization and DNA filament severing or by virtue of actin depolymerization increasing the effectiveness of dornase alf

Hyperspectral Technologies for Assessing Seed Germination and Trifloxysulfuron-methyl Response in Amaranthus palmeri (Palmer Amaranth).

Weed infestations in agricultural systems constitute a serious challenge to agricultural sustainability and food security worldwide. Amaranthus palmeri S. Watson (Palmer amaranth) is one of the most noxious weeds causing significant yield reductions in various crops. The ability to estimate seed viability and herbicide susceptibility is a key factor in the development of a long-term management strategy, particularly since the misuse of herbicides is driving the evolution of herbicide response in various weed species. The limitations of most herbicide response studies are that they are conducted retrospectively and that they use in vitro destructive methods. Development of a non-destructive method for the prediction of herbicide response could vastly improve the efficacy of herbicide applications and potentially delay the evolution of herbicide resistance. Here, we propose a toolbox based on hyperspectral technologies and data analyses aimed to predict A. palmeri seed germination and response to the herbicide trifloxysulfuron-methyl. Complementary measurement of leaf physiological parameters, namely, photosynthetic rate, stomatal conductence and photosystem II efficiency, was performed to support the spectral analysis. Plant response to the herbicide was compared to image analysis estimates using mean gray value and area fraction variables. Hyperspectral reflectance profiles were used to determine seed germination and to classify herbicide response through examination of plant leaves. Using hyperspectral data, we have successfully distinguished between germinating and non-germinating seeds, hyperspectral classification of seeds showed accuracy of 81.9 and 76.4%, respectively. Sensitive and resistant plants were identified with high degrees of accuracy (88.5 and 90.9%, respectively) from leaf hyperspectral reflectance profiles acquired prior to herbicide application. A correlation between leaf physiological parameters and herbicide response (sensitivity/resistance) was also demonstrated. We demonstrated that hyperspectral reflectance analyses can provide reliable information about seed germination and levels of susceptibility in A. palmeri. The use of reflectance-based analyses can help to better understand the invasiveness of A. palmeri, and thus facilitate the development of targeted control methods. It also has enormous potential for impacting environmental management in that it can be used to prevent ineffective herbicide applications. It also has potential for use in mapping tempo-spatial population dynamics in agro-ecological landscapes

Hyperspectral Technologies for Assessing Seed Germination and Trifloxysulfuron-methyl Response in Amaranthus palmeri (Palmer Amaranth).

Weed infestations in agricultural systems constitute a serious challenge to agricultural sustainability and food security worldwide. Amaranthus palmeri S. Watson (Palmer amaranth) is one of the most noxious weeds causing significant yield reductions in various crops. The ability to estimate seed viability and herbicide susceptibility is a key factor in the development of a long-term management strategy, particularly since the misuse of herbicides is driving the evolution of herbicide response in various weed species. The limitations of most herbicide response studies are that they are conducted retrospectively and that they use in vitro destructive methods. Development of a non-destructive method for the prediction of herbicide response could vastly improve the efficacy of herbicide applications and potentially delay the evolution of herbicide resistance. Here, we propose a toolbox based on hyperspectral technologies and data analyses aimed to predict A. palmeri seed germination and response to the herbicide trifloxysulfuron-methyl. Complementary measurement of leaf physiological parameters, namely, photosynthetic rate, stomatal conductence and photosystem II efficiency, was performed to support the spectral analysis. Plant response to the herbicide was compared to image analysis estimates using mean gray value and area fraction variables. Hyperspectral reflectance profiles were used to determine seed germination and to classify herbicide response through examination of plant leaves. Using hyperspectral data, we have successfully distinguished between germinating and non-germinating seeds, hyperspectral classification of seeds showed accuracy of 81.9 and 76.4%, respectively. Sensitive and resistant plants were identified with high degrees of accuracy (88.5 and 90.9%, respectively) from leaf hyperspectral reflectance profiles acquired prior to herbicide application. A correlation between leaf physiological parameters and herbicide response (sensitivity/resistance) was also demonstrated. We demonstrated that hyperspectral reflectance analyses can provide reliable information about seed germination and levels of susceptibility in A. palmeri. The use of reflectance-based analyses can help to better understand the invasiveness of A. palmeri, and thus facilitate the development of targeted control methods. It also has enormous potential for impacting environmental management in that it can be used to prevent ineffective herbicide applications. It also has potential for use in mapping tempo-spatial population dynamics in agro-ecological landscapes