Small Sample Research Articles

In vitro gastrointestinal simulated digestion of three plant proteins: determination of digestion rate, free amino acids and peptide contents

ABSTRACT Cassava protein (CP), barley protein (BP) and yellow pea protein (YPP) are important nutrient and integral constituent of staple in pet foods. It is known that the digestion of proteins directly influences their absorption and utilisation. In the present work, we performed in vitro simulated gastrointestinal digestion of three plant proteins as a staple for dog and cat food. The digestion rate of CP, BP and YPP in dog food was 56.33 ± 0.90%, 48.53 ± 0.91%, and 66.96 ± 0.37%, respectively, whereas the digestion rate of CP, BP, and YPP in cat food was 66.25 ± 0.72%, 43.42 ± 0.83%, and 58.05 ± 0.85%, respectively. Using SDS-polyacrylamide gel electrophoresis to determine the molecular weight (MW) of each protein and the products of their digestion, it was revealed that MW of digestion samples decreased, and MW during the small intestine phase was lower than that during the gastric phase. Peptide sequences of digested products were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and it was found that the total number of peptides in the small intestine digestion samples was higher than that in the gastric phase samples. The MW of peptides obtained from CP was within the range of 1000–1500 Da, while MW of peptides derived from BP and YPP was within the range of 400–2000 Da. In addition, free amino acids were mainly produced in the small intestine phase. Furthermore, the percentage of essential amino acids in the small intestine phase (63 ~ 82%) was higher than that in the gastric phase (37 ~ 63%). Taken together, these findings contribute to the current understanding of the utilisation of plant proteins in dog and cat foods and provide important insights into the selection and application of plant proteins as a staple in dog and cat foods.

Cancer-related pain in head and neck cancer survivors: longitudinal findings from the Head and Neck 5000 clinical cohort.

Reports suggest pain is common in head and neck cancer (HNC). However, past studies are limited by small sample sizes and design and measurement heterogeneity. Using data from the Head and Neck 5000 longitudinal cohort, we investigated pain over a year post-diagnosis. We assessed: temporal trends; compared pain across HNC treatments, stages, sites and by HPV status; and identified subgroups of patients at increased risk of pain. Sociodemographic and clinical data and patient-reported pain (measured by EORTC QLQ-C30 and QLQ-H&N35) were collected at baseline (pre-treatment), 4- and 12- months. Using mixed effects multivariable regression, we investigated time trends and identified associations between (i) clinically-important general pain and (ii) HN-specific pain and clinical, socio-economic, and demographic variables. 2,870 patients were included. At baseline, 40.9% had clinically-important general pain, rising to 47.6% at 4-months and declining to 35.5% at 12-months. HN-specific pain followed a similar pattern (mean score (sd): baseline 26.4 (25.10); 4-months. 28.9 (26.55); 12-months, 17.2 (19.83)). Across time, general and HN-specific pain levels were increased in: younger patients, smokers, and those with depression and comorbidities at baseline, and more advanced, oral cavity and HPV negative cancers. There is high prevalence of general pain in people living with HNC. We identified subgroups more often reporting general and HN-specific pain towards whom interventions could be targeted. Greater emphasis should be placed on identifying and treating pain in HNC. Systematic pain screening could help identify those who could benefit from an early pain management plan.

Automated monitoring of early life‐stage development in Atlantic cod (Gadus morhua) embryos exposed to a reference toxicant

AbstractEarly life stages of fish are widely used for regulatory toxicity testing, and marine fish display high sensitivity to pollutant exposure. Exposure to pollutants during embryogenesis causes acute effects on embryonic development and survival, but also sub‐lethal impacts manifested as maldeveloped larvae. Acquiring time‐ and exposure‐dependent responses to pollutant exposure and other stressors in small organisms is labor intensive and often subjective. This leads to studies obtaining small sample sizes, with measurements often made infrequently during development. Automated monitoring methods can maintain consistency between measurements and allow many more measurements to be made, improving the quantity and quality of such data. We exposed Atlantic cod embryos to 3,4‐dichloroaniline, a reference chemical widely used as a positive control agent in regulatory fish embryo toxicity testing. We monitored their growth through daily imaging with an automated flow‐through imaging system. Biologically relevant sublethal endpoints were estimated from these images with a neural network and traditional machine vision methods. We demonstrate the automated capture and analysis of tens of thousands of images, producing detailed morphometric data from hundreds of fish over a 10‐d study period, and assess the effectiveness of the automated system. The automated method presented allows measurements to be made frequently without sacrificing the sampled organisms, making detailed time series of development obtainable. We show dose‐dependent effects of the toxicant on development and capture nonlinear responses that would not be attainable under a conventional manual sampling regime.

The Level of Knowledge of Decompression Sickness among Divers in Saudi Arabia – A Cross-sectional Study

Abstract Introduction: Decompression sickness (DCS) is a clinical syndrome, i.e. commonly seen in divers. The global prevalence of DCS among professional dive instructors is approximately 3.4%. This study aimed to assess the level of knowledge concerning DCS among divers in Saudi Arabia. Materials and Methods: This is a cross-sectional study conducted among divers in Saudi Arabia. The research team visited several diving resorts to distribute the questionnaires. Furthermore, diving instructors from different cities across the nation were requested to distribute the questionnaire to their colleagues and diving communities. Results: A total of 262 divers participated in the study, of which 252 (96.18%) had a scuba-certified license. The majority of divers (94.27%) reported that they were aware of DCS. Furthermore, 27.48% of the participants reported that they had experienced clinical symptoms of DCS. Only 14 (19.44%) received first aid care, and 17 (6.489%) needed a deco dive/decompression dive. Females demonstrated a higher risk of developing DCS-related symptoms than males (odds ratio = 2.57; 95% confidence interval = 5.44–1.21; P = 0.0135). Conclusion: Majority of the participants were familiar with the nature of the disease and were found to have practiced safe diving. Practically, one-quarter of the participants experienced DCS-related symptoms, and only very few of them received first aid and/or a deco dive. Despite the nature of the study and its small sample size, this study adds to the growing nature of published literature in giving a better understanding of the disease by divers.

Feasibility of Guided Internet-Based Cognitive Behavioral Therapy for Panic Disorder and Social Anxiety Disorder in Japan: Pilot Single-Arm Trial.

Cognitive behavioral therapy (CBT) is effective in treating anxiety disorders. Accessibility to CBT has been limited in Japan due to the shortage of therapists. While an open-source e-learning system can be used to create a simple internet-based cognitive behavioral therapy (ICBT) program, the safety and outpatient acceptance of this treatment approach have not been explored in Japan. The aim of this study was to investigate whether outpatients with anxiety disorders could accept and successfully complete the ICBT program with guidance by CBT therapists when implementing therapeutic modules and CBT tasks. Due to being in the initial phase of a novel treatment in Japan, this study was intended for verification with a small sample size. In total, 6 adults, including 4 male participants and 2 female participants, were enrolled in a single-arm trial. The intervention involved guided ICBT comprising 12 sessions, including CBT text, comprehension confirmation tests, and explanatory videos about cognitive behavioral models, accessible through a website. The therapist guided the participants in accessing the ICBT program and answering their questions using a chat tool. The primary outcome was anxiety severity assessed using the State-Trait Anxiety Inventory-Trait. Secondary outcomes included the Panic Disorder Severity Scale, Liebowitz Social Anxiety Scale (LSAS), Beck Anxiety Inventory (BAI), Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Working Alliance Inventory-Short Form (WAI-SF). Statistical analyses were performed using paired 2-tailed t tests to assess the changes in clinical symptoms. The total WAI-SF score at the final session was used to evaluate the therapeutic alliance. For statistical analyses, mean changes for total State-Trait Anxiety Inventory-Trait, BAI, Panic Disorder Severity Scale, LSAS, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7 scores were analyzed using the paired 2-tailed t test. The 2-sided significance level for hypothesis testing was set at 5%, and 2-sided 95% CIs were calculated. Most participants diligently engaged with the ICBT program. No adverse events were reported. The mean total scores for the primary outcome decreased by 11.0 (SD 9.6) points (95% CI -22.2 to 0.20; Hedges g=0.95), but it was not statistically significant. The mean total scores for the secondary outcomes that assess clinical symptoms decreased, with a significant reduction observed in the BAI of 15.7 (SD 12.1) points (95% CI -28.4 to -3.0; P=.03; Hedges g=1.24). The mean total scores for PDSS and LSAS decreased significantly, by 12.0 (SD 4.24) points (95% CI -50.1 to 26.1; P=.16; Hedges g=1.79) and 32.4 (SD 11.1) points (95% CI -59.7 to -4.3; P=.04; Hedges g=1.38), respectively. Of the participants, 67% (n=4) showed treatment response, and 50% (n=3) achieved remission after the intervention. The therapeutic alliance, measured using the WAI-SF, was moderate. Guided ICBT may be feasible for the treatment of outpatients with panic disorder and social anxiety disorder in Japan. University Hospital Medical Information Network Clinical Trials Registry UMIN0000038118; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000043439.

Quantification of Circulating Cell-Free DNA in Idiopathic Parkinson's Disease Patients.

Parkinson's disease (PD) is one of the most common neurodegenerative disorders globally and leads to an excessive loss of dopaminergic neurons in the substantia nigra of the brain. Circulating cell-free DNA (ccf-DNA) are double-stranded DNA fragments of different sizes and origins that are released into the serum and cerebrospinal fluid (CSF) due to cell death (i.e., necrosis and apoptosis) or are actively released by viable cells via exocytosis and NETosis. Using droplet digital polymerase chain reaction (ddPCR), we comprehensively analyzed and distinguished circulating cell-free mitochondrial DNA (ccf mtDNA) and circulating cell-free nuclear DNA (ccfDNA) in the serum and CSF of PD and control patients. The quantitative analysis of serum ccf-DNA in PD patients demonstrated a significant increase in ccf mtDNA and ccfDNA compared to that in healthy control patients and a significantly higher copy of ccf mtDNA when compared to ccfDNA. Next, the serum ccf mtDNA levels significantly increased in male PD patients compared to those in healthy male controls. Furthermore, CSF ccf mtDNA in PD patients increased significantly compared to ccfDNA, and ccf mtDNA decreased in PD patients more than it did in healthy controls. These decreases were not statistically significant but were in agreement with previous data. Interestingly, ccf mtDNA increased in healthy control patients in both serum and CSF as compared to ccfDNA. The small sample size of serum and CSF were the main limitations of this study. To the best of our knowledge, this is the first comprehensive study on serum and CSF of PD patients using ddPCR to indicate the distribution of the copy number of ccf mtDNA as well as ccfDNA. If validated, we suggest that ccf mtDNA has greater potential than ccfDNA to lead the development of novel treatments for PD patients.

Fuzzy Radar Evaluation Chart for Improving Machining Quality of Components

Some studies have shown that any part machined by an outsourcer usually has several basic quality characteristics. When the outsourcer’s process capabilities are insufficient, the defective rate of various quality characteristics of the product will increase, thereby raising the rework rate and scrap rate. As a result, maintenance costs will go up, economic value will decrease, and even carbon emissions can increase during the production process. In addition, the process capability index and the radar chart are widely used in engineering management and other fields. Since process indicators often contain unknown parameters, sample data are needed for evaluation. With the rapid development of the Internet of Things and big data analysis, many companies regard rapid response as a basic requirement for timeliness and cost consideration. Therefore, companies often have to evaluate the process quality of ten small samples and decide whether to make some improvements. In order to solve the above problems, this study proposed a fuzzy radar chart evaluation model for the process quality of multi-quality characteristic parts based on the process capability index. Using this model can help all parts manufacturers continue to improve the quality of their machined parts as well as reduce their rework and scrap rates. Meanwhile, carbon emissions can be lessened during the production process, and companies can fulfill their social responsibilities. This fuzzy radar chart evaluation model is based on confidence intervals. As the company’s past experience is incorporated, the evaluation accuracy can be maintained even with a smaller sample size. Furthermore, the fuzzy radar evaluation chart can simultaneously evaluate the process capabilities of all quality characteristics of the part. In addition to making it easier for manufacturers to master all quality characteristics, quality process capability can also help them seize improvement opportunities.

Dental health in the adult population of Arkhangelsk: а study protocol

BACKGROUND: The Arkhangelsk region is characterized by a high prevalence and intensity of dental diseases among adults, but most of the studies were either hospital-based or used small samples with questionable representativeness.
 AIM: This article is a protocol of an original study, the purpose of which is to assess the dental status and its association with somatic health in a representative sample of the adult population of Arkhangelsk.
 MATERIAL AND METHODS: In 2022, a cross-sectional study “Prevalence of dental pathology among the population of the Arctic zone of the Russian Federation (using the example of Arkhangelsk) and associated characteristics of the microbiome of the intestine and the respiratory tract” (hereinafter referred to as the dental study) was conducted in Arkhangelsk. The dental study was a part of the study “Molecular and genetic markers of the response to coronavirus infection and changes in the human microbiota and metabolome during the COVID-19 pandemic” (hereinafter referred to as the study on the effects of COVID-19). Data collection for the study was carried out from October 3 to November 10, 2022 at the Northern State Medical University. The study involved 463 adults aged 42–76 years living in the city of Arkhangelsk, representing a random sample of the adult population who had previously taken part in the “Know Your Heart” project in 2015–2017. All participants were asked to undergo an additional dental examination. The response rate was 91.6%. The dental examination included a questionnaire, assessment of dental status as recommended by the World Health Organization (2013), assessment of oral hygiene and gum inflammation, dental aesthetic index (DAI), collection of gingival fluid, autofluorescence stomatoscopy (AFS), examination by an orthodontist with periotestometry, performing a photo protocol, conducting biometrics of plaster models. When indicated, participants were asked to undergo an in-depth diagnostic to identify orthodontic pathology, namely, teleradiography and a cone-beam computed tomography.
 EXPECTED RESULTS: The proposed study using validated instruments and a representative sample has a major strength in providing unbiased assessment of the prevalence of oral health conditions in Arkhangelsk in the studied age group. Moreover, the material collected in this study has a potential to provide a unique opportunity to assess the associations between dental health and somatic health, lifestyle, microbiota, and metabolome since the data on the abovementioned characteristics were collected during the other projects and stored in a biobank.

Strengthening of Laminated Veneer Lumber Slabs with Fiber-Reinforced Polymer Sheets—Preliminary Study

Analyzing the feasibility of reinforcing new and existing wooden structures is a valid problem, being the subject of numerous scientific papers. The paper presents the preliminary results of a study on reinforcing Laminated Veneer Lumber (LVL) panels with composite materials bonded to exterior surfaces using epoxy resin. Glass-Fiber-Reinforced Polymer (GFRP) sheets, Carbon-Fiber-Reinforced Polymer (CFRP) sheets, and Ultra-High-Modulus (UHM) CFRP sheets were used as reinforcement. The variables in the analysis were the type of reinforcement and the number of reinforcement layers. The tests were carried out on small samples (45 × 45 × 900 mm) subjected to the so-called four-point bending test. Reinforcement positively affected the mechanical properties of composite section. The highest increases in load bearing were 37 and 48% for two layers of GFRP and CFRP, respectively. The bending stiffness increased up to 53 and 62% for two layers of CFRP and UHM CFRP, respectively. There was a change in failure mode from cracking in the tension zone for unreinforced beams to veneer shear in the support zone (for CFRP and GFRP sheets) and sheet rupture (UHM CFRP). Good agreement was obtained for estimating bending stiffness with the presented numerical and mathematical model; the relative error was up to 6% for CFRP and GFRP and up to 20% for UHM CFRP. This preliminary study proved the effectiveness of combining LVL with FRP sheets and indicated their weak spots, which should be further analyzed to improve their competitiveness against the traditional structures. The key limitation was the shear strength of LVL.

An automated process for bulk downloading optical coherence tomography scans.

To develop an automated method for efficiently downloading a large number of optical coherence tomography (OCT) scans obtained using the Heidelberg Spectralis (Heidelberg Engineering, Heidelberg, Germany) platform. The electronic medical records and OCT scans were extracted for all patients with age-related macular degeneration treated at the Hadassah University Hospital Retina Clinic between 2010 and 2021. A macro was created using Visual Basic for Applications (VBA) and Microsoft Excel to automate the export process and anonymize the OCT scans in accordance with hospital policy. OCT scans were extracted as proprietary Heidelberg E2E files. The VBA macro was used to export a total of 94,789 E2E files from 2807 patient records, with an average processing time of 4.32 min per volume scan (SD: 3.57 min). The entire export process took a total of approximately 202 h to complete over a period of 24 days. In a smaller sample, using the macro to download the scans was significantly faster than manually downloading the scans, averaging 3.88 vs. 11.08 min/file, respectively (t = 8.59, p < 0.001). Finally, we found that exporting the files during both off-clinic and working hours resulted in significantly faster processing times compared to exporting the files solely during working hours (t = 5.77, p < 0.001). This study demonstrates the feasibility of using VBA and Excel to automate the process for bulk downloading data from a specific medical imaging platform. The specific steps and techniques will likely vary depending on the software used and hospital constraints and should be determined for each application.

Sex-Dependent Changes to the Intestinal and Hepatic Abundance of Drug Transporters and Metabolizing Enzymes in the SOD1G93A Mouse Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is characterized by death and dysfunction of motor neurons that result in a rapidly progressing loss of motor function. While there are some data on alterations at the blood-brain barrier (BBB) in ALS and their potential impact on CNS trafficking of drugs, little is reported on the impact of this disease on the expression of drug-handling proteins in the small intestine and liver. This may impact the dosing of the many medicines that individuals with ALS are prescribed. In the present study, a proteomic evaluation was performed on small intestine and liver samples from postnatal day 120 SOD1G93A mice (a model of familial ALS that harbors a human mutant form of superoxide dismutase 1) and wild-type (WT) littermates (n = 7/genotype/sex). Untargeted, quantitative proteomics was undertaken using either label-based [tandem mass tag (TMT)] or label-free [data-independent acquisition (DIA)] acquisition strategies on high-resolution mass spectrometric instrumentation. Copper chaperone for superoxide dismutase (CCS) was significantly higher in SOD1G93A samples compared to the WT samples for both sexes and tissues, therefore representing a potential biomarker for ALS in this mouse model. Relative to WT mice, male SOD1G93A mice had significantly different proteins (Padj < 0.05, |fold-change|>1.2) in the small intestine (male 22, female 1) and liver (male 140, female 3). This included an up-regulation of intestinal transporters for dietary glucose [solute carrier (SLC) SLC5A1] and cholesterol (Niemann-Pick c1-like 1), as well as for several drugs (e.g., SLC15A1), in the male SOD1G93A mice. There was both an up-regulation (e.g., SLCO2A1) and down-regulation (ammonium transporter rh type b) of transporters in the male SOD1G93A liver. In addition, there was both an up-regulation (e.g., phosphoenolpyruvate carboxykinase) and down-regulation (e.g., carboxylesterase 1) of metabolizing enzymes in the male SOD1G93A liver. This proteomic data set identified male-specific changes to key small intestinal and hepatic transporters and metabolizing enzymes that may have important implications for the bioavailability of nutrients and drugs in individuals with ALS.

Development of non-alcoholic steatohepatitis is associated with gut microbiota but not with oxysterol enzymes CH25H, EBI2, or CYP7B1 in mice

Liver steatosis is the most frequent liver disorder and its advanced stage, non-alcoholic steatohepatitis (NASH), will soon become the main reason for liver fibrosis and cirrhosis. The “multiple hits hypothesis” suggests that progression from simple steatosis to NASH is triggered by multiple factors including the gut microbiota composition. The Epstein Barr virus induced gene 2 (EBI2) is a receptor for the oxysterol 7a, 25-dihydroxycholesterol synthesized by the enzymes CH25H and CYP7B1. EBI2 and its ligand control activation of immune cells in secondary lymphoid organs and the gut. Here we show a concurrent study of the microbial dysregulation and perturbation of the EBI2 axis in a mice model of NASH.We used mice with wildtype, or littermates with CH25H−/−, EBI2−/−, or CYP7B1−/− genotypes fed with a high-fat diet (HFD) containing high amounts of fat, cholesterol, and fructose for 20 weeks to induce liver steatosis and NASH. Fecal and small intestinal microbiota samples were collected, and microbiota signatures were compared according to genotype and NASH disease state.We found pronounced differences in microbiota composition of mice with HFD developing NASH compared to mice did not developing NASH. In mice with NASH, we identified significantly increased 33 taxa mainly belonging to the Clostridiales order and/ or the family, and significantly decreased 17 taxa. Using an Elastic Net algorithm, we suggest a microbiota signature that predicts NASH in animals with a HFD from the microbiota composition with moderate accuracy (area under the receiver operator characteristics curve = 0.64). In contrast, no microbiota differences regarding the studied genotypes (wildtype vs knock-out CH25H−/−, EBI2−/−, or CYP7B1−/−) were observed.In conclusion, our data confirm previous studies identifying the intestinal microbiota composition as a relevant marker for NASH pathogenesis. Further, no link of the EBI2 – oxysterol axis to the intestinal microbiota was detectable in the current study.

SVM bearing fault diagnosis based on fast inter-class distance in the feature space and DMPSO algorithm

Support vector machines (SVMs) have good processing performance for small sample datasets. The giant search space for kernel parameters and the tendency of parameter optimization to fall into local optima are two essential factors that affect the generalization ability of SVM models and, thus, affect the accuracy of fault diagnosis results. Propose using fast inter-class distance (FICDF) in the feature space to reduce the search space for kernel function parameters and then use differential mutation particle swarm optimization (DMPSO) to optimize kernel function parameters to improve the generalization ability and classification accuracy of the SVM model. Firstly, the FICDF algorithm is used to calculate the Euclidean distance between classes, and a fast segmentation idea is proposed for fast operations to obtain a smaller kernel parameter search space. Then, the global search ability of the DMPSO algorithm is used to obtain the optimal parameter combination of the SVM model. Finally, the fault diagnosis model of the SVM is applied to the fault diagnosis of rolling bearings. The experimental results show that compared with other fault diagnosis methods, this model method has higher classification accuracy and verifies its better classification speed.

The Perceived Value of Customers: Antecedents and Its Effect on Word-of-mouth

Purpose: This study aims to investigate the antecedents of the customer's perceived value, including multi-channel integration and brand equity, and the impact of the perceived value on word-of-mouth.&#x0D; Design/methodology/approach: A quantitative approach by PLS-SEM was used in the research. This paper conducted a survey of 414 respondents who are customers of retail firms in Vietnam.&#x0D; Findings: The research results illustrate the significant impact of multi-channel integration and brand equity on the perceived value of customers. The study also found that word-of-mouth is directly and positively influenced by the customer's perceived value.&#x0D; Research limitations/implications: Besides multi-channel integration and brand equity, other factors that may act as antecedents of the perceived value have not been recognized in the study. The study only focuses on the retail industry with a relatively small sample size which is a limitation of the sample representative.&#x0D; Originality/value: This study provides reliable evidence about the important role of building an integrated multi- channel system and nurturing brand equity to increase the perceived value in customer's minds. Additionally, the research reinforces the convincing evidence of the significant and positive relationship between the customer's perceived value and their positive word-of-mouth communication.

A Metric-Based Few-Shot Learning Method for Fish Species Identification with Limited Samples.

Fish species identification plays a vital role in marine fisheries resource exploration, yet datasets related to marine fish resources are scarce. In open-water environments, various fish species often exhibit similar appearances and sizes. To solve these issues, we propose a few-shot learning approach to identifying fish species. Our approach involves two key components. Firstly, the embedding module was designed to address the challenges posed by a large number of fish species with similar phenotypes by utilizing the distribution relationships of species in the embedding space. Secondly, a metric function was introduced, effectively enhancing the performance of fish species classification and successfully addressing the issue of limited sample quantity. The proposed model is trained end to end on fish species public datasets including the Croatian fish dataset, Fish4Knowledge and WildFish. Compared with the prototypical networks, our method performs more effectively and improves accuracy by 2% to 10%; it is able to identify fish effectively in small samples sizes and complex scene scenarios. This method provides a valuable technological tool for the development of fisheries resources and the preservation of fish biodiversity.

Ketamine for Adults With Substance Use Disorders

What Is the Issue&#x0D; &#x0D; Accumulating research has demonstrated that subanesthetic doses of ketamine have rapid and sustained antidepressant effects. In 2019, the US FDA approved the S-enantiomer of ketamine (esketamine) for the treatment of patients with treatment-resistant depression.&#x0D; Since then, there has been interest in the development of ketamine for the treatment of a broad range of mental health conditions beyond depression, including substance use disorders (SUDs).&#x0D; Decision-makers want to know if there is any evidence to support the use of ketamine for treating SUDs in adults.&#x0D; &#x0D; What Did We Do?&#x0D; &#x0D; To inform decisions about using ketamine for treating SUDs, we sought to identify and summarize the literature comparing the clinical and cost-effectiveness of ketamine with placebo or no treatment, with alternative interventions, or among ketamine administered via different routes for SUDs. We also searched for evidence-based recommendations for the use of ketamine for SUDs.&#x0D; A research information specialist conducted a literature search of peer-reviewed and grey literature sources published between January 1, 2018, and November 28, 2023. One reviewer screened citations for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings.&#x0D; &#x0D; What Did We Find?&#x0D; &#x0D; We found 2 systematic reviews (SRs) and 1 randomized controlled trial (RCT) on the use of ketamine for the treatment of patients with alcohol use disorder (AUD), cocaine use disorder (CUD), and opioid use disorder (OUD).&#x0D; Evidence from 2 SR suggests that a combination of ketamine infusion and psychotherapy treatment may be effective in promoting abstinence and reduced consumption of alcohol and cocaine use. There were mixed results regarding the effect of ketamine on withdrawal and craving.&#x0D; The effects of ketamine on OUD were inconclusive as the results were derived from a single study with a small sample size. Similarly, the effects of ketamine on health care utilization (e.g., hospital readmission, emergency department visit) in patients with severe AUD reported in a RCT were also inconclusive due to the small sample size.&#x0D; Adverse events associated with ketamine treatment included the dissociative and psychotomimetic effects and nondissociative effects. The authors of the included SR reported that these events were mild and transient.&#x0D; We did not find any studies on the cost-effectiveness or evidence-based guidelines of ketamine for treating SUDs that met our criteria for this review.&#x0D; &#x0D; What Does It Mean?&#x0D; &#x0D; The conclusions on the positive effects of ketamine for AUD and CUD should be interpreted with caution due to the high risk of bias of the studies included in the SRs.&#x0D; There is a need for more robust clinical trials with larger sample sizes, blinding, and low risk of bias to provide more accurate findings on clinical efficacy, dosing strategies, and safety profile of ketamine for the treatment of AUD, CUD, and OUD.&#x0D; Additional studies on other substances of abuse (e.g., nicotine, amphetamines, and cannabis) may provide important insights into the overall efficacy of ketamine in the treatment of SUDs.&#x0D;

Transfer-Learning-Based Human Activity Recognition Using Antenna Array

Due to its low cost and privacy protection, Channel-State-Information (CSI)-based activity detection has gained interest recently. However, to achieve high accuracy, which is challenging in practice, a significant number of training samples are required. To address the issues of the small sample size and cross-scenario in neural network training, this paper proposes a WiFi human activity-recognition system based on transfer learning using an antenna array: Wi-AR. First, the Intel5300 network card collects CSI signal measurements through an antenna array and processes them with a low-pass filter to reduce noise. Then, a threshold-based sliding window method is applied to extract the signal of independent activities, which is further transformed into time–frequency diagrams. Finally, the produced diagrams are used as input to a pretrained ResNet18 to recognize human activities. The proposed Wi-AR was evaluated using a dataset collected in three different room layouts. The testing results showed that the suggested Wi-AR recognizes human activities with a consistent accuracy of about 94%, outperforming the other conventional convolutional neural network approach.

A MENTAL ILLNESS EARLY WARNING ANALYSIS MODEL USING AN IMPROVED SVM ALGORITHM AND EEG SIGNALS

The fast-paced lifestyle, intense competition, and constantly changing environment of modern society are important factors contributing to the emergence of psychological disorders. Factors such as work pressure, family conflicts, and interpersonal relationship difficulties pose challenges to individual mental health. Prolonged use of electronic devices and the widespread use of social media further exacerbate mental health issues, as the constant influx of information makes it difficult for people to relax and focus. The harm of psychological disorders to individuals and society cannot be ignored. It not only diminishes the quality of life for patients but also affects work efficiency and social participation. In extreme cases, psychological disorders can lead to serious consequences like suicide, causing immense pain to families and society. Therefore, prioritizing mental health, raising awareness of mental well-being, and timely intervention and treatment of psychological disorders are crucial for individual happiness and social stability. Based on this, this study employs an improved Support Vector Machine (SVM) and Electroencephalogram (EEG) signals for the diagnosis of psychological disorders, aiming for more effective treatment of mental health conditions. Specifically, the EEG signals of the experimental subjects are first collected as training data for the model. The dataset undergoes preprocessing operations such as cleaning and normalization. Due to the limited availability of published information about individuals with psychological disorders, an ensemble SVM algorithm is used as a warning model to improve the accuracy of psychological disorder diagnosis. This algorithm utilizes a differential measurement method to adjust the selection of SVM parameters. The training sample size remains constant, with several iterations of training performed. By combining the differential measurement method, a specific parameter combination is obtained, maximizing the differentiation between base classifiers. This ultimately addresses issues such as small sample size and insufficient sample information in the dataset. Experimental results demonstrate that the model used in this study exhibits good performance in diagnosing psychological disorders.

Bayesian estimation of equipment reliability with normal-type life distribution based on multiple batch tests

Abstract The test of new equipment is usually carried out in multiple batches according to the task schedule and test results. Constrained by the test environment, cost, and other factors, the amount of reliability test data in each batch is relatively limited, which brings difficulties to the accurate equipment reliability estimation work. For the reliability simulation tests conducted before each batch tests, it is particularly important to make full use of each batch tests information and simulation tests information to estimate the reliability of the equipment for small sample tests. This study takes the common normal-type life distribution equipment as the research object, and selects the normal-inverse gamma distribution as the equipment life parameters prior distribution based on the Bayesian method. Combined with the system contribution, the fusion weights of each batch tests information are determined and all the batch tests information is fused. Finally, the estimation of equipment reliability based on multiple batch tests is completed. The research results show that this method can integrate the information of each batch test and simulation test, overcome the problem of insufficient information of single batch tests, and provide an effective analytical tool for equipment reliability estimation.

A geometric morphometric approach to distinguish ferret from polecat and its application to an archaeological specimen from Mechelen (Belgium)

The inability to differentiate skeletal remains belonging to the ferret from those of its wild ancestor, the European polecat, presents a particular challenge for zooarchaeologists which currently hinders a better understanding of ferret domestication history. Using a geometric morphometric approach on the mandible, this study provides a new method to distinguish the two forms. Despite a small sample size and some overlap in the dataset, this method allowed the identification of a (post)medieval specimen from Mechelen (Belgium) as a wild polecat. Results demonstrate that ferrets can largely be distinguished from polecats based on mandibular morphology.