Optimised production of technetium-94m for PET imaging by proton-irradiation of phosphomolybdic acid in cyclotron liquid target.

Natural-abundance phosphomolybdic acid (H3(Mo12PO40) ‧12H2O, 0.181-0.552 g Mo/mL) solutions were irradiated with 12.9 MeV protons on a GE PETtrace cyclotron using an adapted standard liquid target. Technetium-94m (94mTc) was produced through the 94Mo(p,n)94mTc nuclear reaction with saturation yields of up to 53 ± 6 MBq/µA. End of bombardment activities of 161 ± 17 MBq and 157 ± 7 MBq were achieved for the 0.552 g Mo/mL solution (10 µA for 30 min) and 0.181 g Mo/mL solution (15 µA for 60 min), respectively. No visible degradation of the niobium target body and foil were seen during the irradiations of up to 15 µA for 60 min. The produced 94mTc was separated from the target phosphomolybdic acid solution with >98% recovery using an aqueous biphasic extraction resin. Compared to previous reported liquid target methods for 94mTc production, the better production yield, in-target solution stability during irradiation and 94mTc separation recovery of phosphomolybdic acid makes it a very promising target material for routine clinical 94mTc production at medical facilities with liquid targets already installed for 18F production.

Correction: Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study.

[This corrects the article DOI: 10.2196/44358.].

Closing the accessibility gap to mental health treatment with a personalized self-referral chatbot.

Inequality in treatment access is a pressing issue in most healthcare systems across many medical disciplines. In mental healthcare, reduced treatment access for minorities is ubiquitous but remedies are sparse. Here we demonstrate that digital tools can reduce the accessibility gap by addressing several key barriers. In a multisite observational study of 129,400 patients within England's NHS services, we evaluated the impact of a personalized artificial intelligence-enabled self-referral chatbot on patient referral volume and diversity in ethnicity, gender and sexual orientation. We found that services that used this digital solution identified substantially increased referrals (15% increase versus 6% increase in control services). Critically, this increase was particularly pronounced in minorities, such as nonbinary (179% increase) and ethnic minority individuals (29% increase). Using natural language processing to analyze qualitative feedback from 42,332 individuals, we found that the chatbot's human-free nature and the patients' self-realization of their need for treatment were potential drivers for the observed improvement in the diversity of access. This provides strong evidence that digital tools may help overcome the pervasive inequality in mental healthcare.

Heart rate variability (HRV) as a way to understand associations between the autonomic nervous system (ANS) and affective states: A critical review of the literature.

Evidence suggests affective disorders such as depression and bipolar disorder are characterised by dysregulated autonomic nervous system (ANS) activity. These findings suggest ANS dysregulation may be involved in the pathogenesis of affective disorders. Different affective states are characterised by different ANS activity patterns (i.e., an increase or decrease in sympathetic or parasympathetic activity). To understand how ANS abnormalities are involved in the development of affective disorders, it is important to understand how affective states correlate with ANS activity before their onset. Using heart rate variability (HRV) as a tool to measure ANS activity, this review aimed to look at associations between affective states and HRV in non-clinical populations (i.e., in those without medical and psychiatric disorders). Searches on PubMed and Google Scholar were completed using the following search terms: heart rate variability, autonomic nervous system, sympathetic nervous system, parasympathetic nervous system, affective state, mood and emotion in all possible combinations. All but one of the studies examined (N = 13), demonstrated significant associations between affect and HRV. Findings suggest negative affect, encompassing both diffused longer-term experiences (i.e., mood) as well as more focused short-term experiences (i.e., emotions), may be associated with a reduction in parasympathetic activity as measured through HRV parameters known to quantify parasympathetic activity (e.g., high frequency (HF)-HRV). HRV measures typically linked to reduction in parasympathetic activity appear to be linked to negative affective states in non-clinical populations. However, given the complex and possibly non-linear relationship between HRV and parasympathetic activity, further studies need to clarify specificity of these findings. Future studies should investigate the potential utility of HRV measures as biomarkers for monitoring changes in affective states and for early detection of onset and relapse of depression in patients with affective disorders.

Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study.

BACKGROUND: Most mental health care providers face the challenge of increased demand for psychotherapy in the absence of increased funding or staffing. To overcome this supply-demand imbalance, care providers must increase the efficiency of service delivery. OBJECTIVE: In this study, we examined whether artificial intelligence (AI)-enabled digital solutions can help mental health care practitioners to use their time more efficiently, and thus reduce strain on services and improve patient outcomes. METHODS: In this study, we focused on the use of an AI solution (Limbic Access) to support initial patient referral and clinical assessment within the UK's National Health Service. Data were collected from 9 Talking Therapies services across England, comprising 64,862 patients. RESULTS: We showed that the use of this AI solution improves clinical efficiency by reducing the time clinicians spend on mental health assessments. Furthermore, we found improved outcomes for patients using the AI solution in several key metrics, such as reduced wait times, reduced dropout rates, improved allocation to appropriate treatment pathways, and, most importantly, improved recovery rates. When investigating the mechanism by which the AI solution achieved these improvements, we found that the provision of clinically relevant information ahead of clinical assessment was critical for these observed effects. CONCLUSIONS: Our results emphasize the utility of using AI solutions to support the mental health workforce, further highlighting the potential of AI solutions to increase the efficiency of care delivery and improve clinical outcomes for patients.

How Many Clocks, How Many Times? On the Sensory Basis and Computational Challenges of Circadian Systems.

A vital task for every organism is not only to decide what to do but also when to do it. For this reason, "circadian clocks" have evolved in virtually all forms of life. Conceptually, circadian clocks can be divided into two functional domains; an autonomous oscillator creates a ~24 h self-sustained rhythm and sensory machinery interprets external information to alter the phase of the autonomous oscillation. It is through this simple design that variations in external stimuli (for example, daylight) can alter our sense of time. However, the clock's simplicity ends with its basic concept. In metazoan animals, multiple external and internal stimuli, from light to temperature and even metabolism have been shown to affect clock time. This raises the fundamental question of cue integration: how are the many, and potentially conflicting, sources of information combined to sense a single time of day? Moreover, individual stimuli, are often detected through various sensory pathways. Some sensory cells, such as insect chordotonal neurons, provide the clock with both temperature and mechanical information. Adding confusion to complexity, there seems to be not only one central clock in the animal's brain but numerous additional clocks in the body's periphery. It is currently not clear how (or if) these "peripheral clocks" are synchronized to their central counterparts or if both clocks "tick" independently from one another. In this review article, we would like to leave the comfort zones of conceptual simplicity and assume a more holistic perspective of circadian clock function. Focusing on recent results from Drosophila melanogaster we will discuss some of the sensory, and computational, challenges organisms face when keeping track of time.

Light Dominates Peripheral Circadian Oscillations in Drosophila melanogaster During Sensory Conflict.

In Drosophila, as in other animals, the circadian clock is a singular entity in name and concept only. In reality, clock functions emerge from multiple processes and anatomical substrates. One distinction has conventionally been made between a central clock (in the brain) and peripheral clocks (e.g., in the gut and the eyes). Both types of clock generate robust circadian oscillations, which do not require external input. Furthermore, the phases of these oscillations remain exquisitely sensitive to specific environmental cues, such as the daily changes of light and temperature. When these cues conflict with one another, the central clock displays complex forms of sensory integration; how peripheral clocks respond to conflicting input is unclear. We therefore explored the effects of light and temperature misalignments on peripheral clocks. We show that under conflict, peripheral clocks preferentially synchronize to the light stimulus. This photic dominance requires the presence of the circadian photoreceptor, Cryptochrome.

Sensory Conflict Disrupts Activity of the Drosophila Circadian Network.

Periodic changes in light and temperature synchronize the Drosophila circadian clock, but the question of how the fly brain integrates these two input pathways to set circadian time remains unanswered. We explore multisensory cue combination by testing the resilience of the circadian network to conflicting environmental inputs. We show that misaligned light and temperature cycles can lead to dramatic changes in the daily locomotor activities of wild-type flies during and after exposure to sensory conflict. This altered behavior is associated with a drastic reduction in the amplitude of PERIOD (PER) oscillations in brain clock neurons and desynchronization between light- and temperature-sensitive neuronal subgroups. The behavioral disruption depends heavily on the phase relationship between light and temperature signals. Our results represent a systematic quantification of multisensory integration in the Drosophila circadian system and lend further support to the view of the clock as a network of coupled oscillatory subunits.

Identification of dominant odor chemicals emanating from explosives for use in developing optimal training aid combinations and mimics for canine detection.

Despite the recent surge in the publication of novel instrumental sensors for explosives detection, canines are still widely regarded as one of the most effective real-time field method of explosives detection. In the work presented, headspace analysis is performed by solid phase microextraction (SPME)/gas chromatography-mass spectrometry (GC-MS), and gas chromatography-electron capture detection (GC-ECD), and used to identify dominant explosive odor chemicals seen at room temperature. The activity of the odor chemicals detected was determined through field trials using certified law enforcement explosives detection canines. A chemical is considered an active explosive odor when a trained and certified explosives detection canine alerts to a sample containing that target chemical (with the required controls in place). A sample to which the canine does not alert may be considered an inactive odor, but it should be noted that an inactive odor might still have the potential to enhance an active odor's effect. The results presented indicate that TNT and cast explosives share a common odor signature, and the same may be said for plasticized explosives such as Composition 4 (C-4) and Detasheet. Conversely, smokeless powders may be demonstrated not to share common odors. The implications of these results on the optimal selection of canine training aids are discussed.

Laboratory and field experiments used to identify Canis lupus var. familiaris active odor signature chemicals from drugs, explosives, and humans.

This paper describes the use of headspace solid-phase microextraction (SPME) combined with gas chromatography to identify the signature odors that law enforcement-certified detector dogs alert to when searching for drugs, explosives, and humans. Background information is provided on the many types of detector dog available and specific samples highlighted in this paper are the drugs cocaine and 3,4-methylenedioxy- N-methylamphetamine (MDMA or Ecstasy), the explosives TNT and C4, and human remains. Studies include the analysis and identification of the headspace "fingerprint" of a variety of samples, followed by completion of double-blind dog trials of the individual components in an attempt to isolate and understand the target compounds that dogs alert to. SPME-GC/MS has been demonstrated to have a unique capability for the extraction of volatiles from the headspace of forensic specimens including drugs and explosives and shows great potential to aid in the investigation and understanding of the complicated process of canine odor detection. Major variables evaluated for the headspace SPME included fiber chemistry and a variety of sampling times ranging from several hours to several seconds and the resultant effect on ratios of isolated volatile components. For the drug odor studies, the CW/DVB and PDMS SPME fibers proved to be the optimal fiber types. For explosives, the results demonstrated that the best fibers in field and laboratory applications were PDMS and CW/DVB, respectively. Gas chromatography with electron capture detector (GC/ECD) and mass spectrometry (GC/MS) was better for analysis of nitromethane and TNT odors, and C-4 odors, respectively. Field studies with detector dogs have demonstrated possible candidates for new pseudo scents as well as the potential use of controlled permeation devices as non-hazardous training aids providing consistent permeation of target odors.