Considerable variation in feed efficiency (FE) has been observed in indigenous and selected meat-type chicken populations. Although this variation could be partially linked to extrinsic factors like diet, housing environment and microbiota, it further illustrates the existence of strong molecular mechanisms enabling the differential allocation of resources for various physiological processes. To further deepen the molecular basis of individual allocation capacity in male and female broilers, an RNA-seq experiment was conducted which based on a phenotyped chicken population divergent in FE. Transcriptional differences linked to FE were pronounced in intestinal and muscular tissue sites of male animals. Specifically, signalling pathways of farnesoid X receptor (FXR) and retinoid X receptor (RXR) might contribute to mediate individual FE. The transcriptional profiles suggested ACSBG2 (muscular lipid utilisation), ASBT (intestinal bile salt transport), CLEC2B (natural killer cell activation), HMGCS2 (jejunal, duodenal and muscular ketogenesis), and SCARB1 (jejunal lipid uptake) as potential mediators driving FE. Results indicate that improvements in FE exploit shifts in resource allocation which might occur at the expense of general immune responsiveness in high efficient male chickens. Consequently, to further improve FE traits and to explore causative molecular patterns, effects originating from sex-dimorphism in chickens need to be taken into consideration.

In the dairy industry, mate allocation is dependent on the producer's breeding goals and the parents' breeding values. The probability of pregnancy differs among sire-dam combinations, and the compatibility of a pair may vary due to the combination of gametic haplotypes. Under the hypothesis that incomplete incompatibility would reduce the odds of fertilization, and complete incompatibility would lead to a non-fertilizing or lethal combination, deviation from Mendelian inheritance expectations would be observed for incompatible pairs. By adding an interaction to a transmission ratio distortion (TRD) model, which detects departure from the Mendelian expectations, genomic regions linked to gametic incompatibility can be identified. This study aimed to determine the genetic background of gametic incompatibility in Holstein cattle. A total of 283,817 genotyped Holstein trios were used in a TRD analysis, resulting in 422 significant regions, which contained 2075 positional genes further investigated for network, overrepresentation, and guilt-by-association analyses. The identified biological pathways were associated with immunology and cellular communication and a total of 16 functional candidate genes were identified. Further investigation of gametic incompatibility will provide opportunities to improve mate allocation for the dairy cattle industry.

Displaced intracapsular femoral neck (AO type 31 B2/3) fractures have various treatments, including internal fixation (IF), unipolar uncemented hemiarthroplasty (HA), bipolar uncemented HA, unipolar cemented HA, bipolar cemented HA, uncemented total hip replacement (THR), and cemented THR. Systematic literature retrieval was performed from the databases to compare them in a network meta-analysis. Forty studies (85 arms) containing 6141 patients were included. Overall, our network meta-analysis rank the orders of 7 procedures in reoperation, mortality, dislocation and infection, which indicates that IF may provide the highest reoperation incidence, unipolar cemented HA may provide the lowest reoperation incidence; uncemented THR contributes the highest dislocation incidence; and bipolar uncemented HA provides the lowest infection incidence. No differences in mortality were observed among the treatments. This conclusion is indirect; higher-quality direct comparisons are required.

Placebos have been shown to be beneficial for various conditions even if administered with full transparency. Hence, so-called open-label placebos (OLPs) offer a new way to harness placebo effects ethically. To take this concept one step further, this study aimed at evaluating placebo effects without the use of a physical placebo, i.e., by imagining taking a pill. Healthy students (N = 173) with self-reported test anxiety were either randomized to an imaginary pill (IP; n = 55), an OLP (n = 59) or a control group (CG; n = 59). Both intervention groups were instructed to take two pills daily for three weeks. Primary outcome was test anxiety, secondary outcomes were sleep quality, general well-being and test performance. Groups test anxiety differed at study-endpoint, F(2,169) = 11.50, p < .001. Test anxiety was lower in the intervention groups compared to the CG, t(169) = - 4.44, p < .001, d = - 0.71. The interventions did not differ significantly, i.e., both were similarly efficacious, t(169) = 0.61, p = .540, d = 0.11. The interaction between group and time in explaining test anxiety was significant, F(5,407.93) = 6.13, p < .001. OLPs and IPs reduced test anxiety in healthy participants compared to the CG. This finding opens the door for a novel and ethical method to harness placebo effects.

The thermal grill illusion (TGI) is assumed to result from crosstalk between the thermoreceptive and nociceptive pathways. To elucidate this further, we compared 40 female fibromyalgia patients to 20 healthy women in an exploratory cross-sectional study. Sensations (cold, warm/heat, unpleasantness, pain and burning) evoked by 20 °C, 40 °C and alternating 20 °C/40 °C (TGI) and somatosensory profiles according to standardized quantitative sensory testing (QST) were assessed on the palm of the dominant hand. Compared to healthy controls, fibromyalgia patients reported stronger thermal grill-evoked cold, warm, unpleasantness and pain as well as stronger and more aversive 20 °C- and 40 °C-evoked sensations. They showed a loss in warm, mechanical and vibration detection, a gain in thermal pain thresholds and higher temporal summation (TS). Among QST parameters higher TS in fibromyalgia patients was most consistently associated with an augmented TGI. Independently, an increased TGI was linked to cold (20 °C) but less to warm (40 °C) perception. In fibromyalgia patients all thermal grill-evoked sensations were positively related to a higher 20 °C-evoked cold sensation and/or 20 °C-evoked unpleasantness. In conclusion, the TGI appears to be driven mainly by the cold-input. Aversive cold processing and central pain facilitation in fibromyalgia patients seem to independently augment the activation of the pain pathway.

The effects of long-term omega-3 polyunsaturated fatty acid (n-3 PUFA) supplementation during endurance training on tryptophan (Trp) metabolism and mental state of healthy individuals have not been evaluated so far. Concentrations of plasma Trp, its metabolites and IL-6 were assessed in 26 male runners before and after a 12-week training program combined with supplementation of n-3 PUFAs (O-3 + TRAIN group) or medium chain triglycerides (MCTs; TRAIN group). After the 12-week program participants' mood before and after stress induction was also assessed. The effects of the same supplementation protocol were evaluated also in 14 inactive subjects (O-3 + SEDEN group). Concentrations of 3-hydroxykynurenine (3-HK) and picolinic acid (PA) significantly increased only in the O-3 + TRAIN group (p = 0.01; [Formula: see text] = 0.22 and p = 0.01; [Formula: see text]= 0.26). Favorable, but not statistically significant changes in the concentrations of kynurenic acid (KYNA) (p = 0.06; [Formula: see text]= 0.14), xanthurenic acid (XA) (p = 0.07; [Formula: see text]= 0.13) and 3-hydroxyanthranilic acid (3-HAA) (p = 0.06; [Formula: see text]= 0.15) and in the ratio of neurotoxic to neuroprotective metabolites were seen also only in the O-3 + TRAIN group. No changes in mood and IL-6 concentrations were observed in either group. Supplementation with n-3 PUFAs during endurance training has beneficial effects on Trp's neuroprotective metabolites.Trial registry: This study was registered at ClinicalTrials.gov with identifier NCT05520437 (14/07/2021 first trial registration and 2018/31/N/NZ7/02962 second trial registration).

Various techniques have been formulated to reduce pain and ensure early recovery after surgery, as these are major concerns among surgeons, anesthesiologists, and patients. Erector spinae plane block (ESPB), the injection of local anesthetic into the fascial plane, is a simple and novel analgesia technique widely used due to its minimal risk of complications. ESPB has been tried in various surgeries; however, no study has reported its use in colorectal surgery. This study investigated whether ESPB could promote early recovery following laparoscopic colorectal surgery (LCS) by reducing opioid consumption and pain intensity. After randomization into the ESPB or control groups, an ultrasound-guided ESPB was performed at the thoracic 10th-11th level with 40 mL of 0.25% bupivacaine or normal saline. The ESPB group used less fentanyl during the initial 24 h after surgery (P = 0.004) and experienced less pain (P < 0.05 at all-time points) than the control group. The time to the first ambulation and the length of hospital stay were shorter in the ESPB group than in the control group (P = 0.015 and P = 0.008, respectively). In conclusion, ESPB could promote early recovery by reducing opioid consumption and pain intensity in patients receiving LCS.

Precordial Doppler ultrasound technology can be utilized to confirm correct peripheral intravenous vascular (PIV) access in children during surgery. This study aimed to determine the minimally required dose of normal saline (NS) for confirming correct PIV access. Healthy children were randomly allocated to receive a 0.1 mL/kg, 0.3 mL/kg, or 0.5 mL/kg dose of NS injected via PIV access. Two independent raters judged the change in the recorded precordial Doppler sound test (S-test) before and after NS injection. Typically, rapid injection of NS increased the pitch of the heartbeat as the injection volume increased. Changes in blood flow velocity test (V-test) results were evaluated using a cut-off value of 1 cm/s. Both in the S- and V-tests, the detection rate of correct PIV access was lower with 0.1 mL/kg NS than with 0.3 mL/kg or 0.5 mL/kg. Logistic regression analysis showed that the positive results in both the S- and V-tests were significantly decreased with a 0.1 mL/kg NS; no significant difference was observed with a 0.3 mL/kg NS (reference dose: 0.5 mL/kg). These results suggest 0.3 mL/kg is the minimally required dose of NS for confirming correct PIV access. This study is registered with the University Hospital Medical Information Network (UMIN000041330).

The omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) affect cell function and metabolism, but the differential effects of EPA and DHA are not known. In a randomized, controlled, double-blind, crossover study, we assessed the effects of 10-week supplementation with EPA-only and DHA-only (3 g/d), relative to a 4-week lead-in phase of high oleic acid sunflower oil (3 g/day, defined as baseline), on fasting serum metabolites in 21 subjects (9 men and 12 post-menopausal women) with chronic inflammation and some characteristics of metabolic syndrome. Relative to baseline, EPA significantly lowered the tricarboxylic acid (TCA) cycle intermediates fumarate and α-ketoglutarate and increased glucuronate, UDP-glucuronate, and non-esterified DHA. DHA significantly lowered the TCA cycle intermediates pyruvate, citrate, isocitrate, fumarate, α-ketoglutarate, and malate, and increased succinate and glucuronate. Pathway analysis showed that both EPA and DHA significantly affected the TCA cycle, the interconversion of pentose and glucuronate, and alanine, and aspartate and glutamate pathways (FDR < 0.05) and that DHA had a significantly greater effect on the TCA cycle than EPA. Our results indicate that EPA and DHA exhibit both common and differential effects on cell metabolism in subjects with chronic inflammation and some key aspects of metabolic syndrome.

Nicotine is an addictive compound that activates neuronal nicotinic acetylcholine receptors (nAChRs) and causes behavioural effects that vary with dose, schedule of administration, and animal model. In zebrafish (Danio rerio), acute doses of nicotine have been consistently found to have anxiolytic properties, whereas, chronic exposure elicits anxiogenic effects. To date, however, studies on repeated nicotine administration and the effects of nicotine withdrawal have not been well explored using this model. In this study, we administered nicotine with three different dosing regimens: 1. Single exposures of a "high" dose (25, 50, 100, or 400 mg/L) for 3 minutes. 2. Single exposures to a "low" dose (2.5, 5, or 20 mg/L) for one hour. 3. Repeated one-hour exposure to a "low" dose (2.5, 5, or 20 mg/L) for 21 days. The novel object approach test was used to examine boldness based on the tendency of the fish to explore a novel object. Acutely, nicotine significantly increased the time spent approaching the object with both three-minute and onehour durations of exposure, indicating increased boldness. Conversely, after repeated nicotine exposure for 21 days, fish spent less time approaching the object suggesting a decrease in boldness. Distance moved was unaffected one hour after repeated nicotine exposure, yet decreased after a two-day withdrawal period. Our work suggests that nicotine can have opposing effects on boldness that vary based on dosage and schedule of exposure.

The majority of individuals with problematic and pathological gambling remain untreated, and treatment barriers are high. Internet-based interventions can help to address existing barriers, and first studies suggest their potential for this target group. Within a randomized controlled trial (N = 150) with two assessment times (baseline and post-intervention), we aimed to investigate the feasibility, acceptance, and effectiveness of a self-guided Internet-based intervention targeted at gambling problems. We expected a significant reduction in gambling symptoms (primary outcome) and depressive symptoms as well gambling-specific dysfunctional thoughts (secondary outcomes) in the intervention group (IG) compared to a wait-list control group with access to treatment-as-usual (control group, CG) after the intervention period of 8 weeks. Results of the complete cases, per protocol, intention-to-treat (ITT), and frequent user analyses showed significant improvements in both groups for primary and secondary outcomes but no significant between-group differences (ITT primary outcome, F(1,147) = .11, p = .739, ηp2 < .001). Moderation analyses indicated that individuals in the IG with higher gambling and depressive symptoms, older age, and comorbid anxiety symptoms showed significant improvement relative to the CG. The intervention was positively evaluated (e.g., 96.5% rated the program as useful). Possible reasons for the nonsignificant between-group differences are discussed. Future studies should include follow-up assessments and larger samples to address limitations of the present study. Trial Registration ClinicalTrials.gov (NCT03372226), http://clinicaltrials.gov/ct2/show/NCT03372226 , date of registration (13/12/2017).

External cephalic version (ECV) is associated with a moderate degree of pain. Virtual reality (VR) is a technology that has shown promise in offering procedural analgesia. We undertook a clinical pilot to assess the viability of VR to reduce pain during ECV. In an open randomised controlled trial (RCT), we randomised 50 women to either VR or standard care each (25 per group). Women receiving VR were administered VR content (Skylights) via a headset. Pre- and post-procedural measures of pain, anxiety, device experience and vital signs were measured. There were no significant differences between groups (VR/no VR) in pain scores (60.68 vs 49.76; p = 0.2), ECV success rates (80% vs 76%; p = 0.7) or anxiety levels. The women receiving VR had a significantly higher anticipation of pain pre-procedurally (70.0 vs 50.0; p = 0.03). 20 (80%) of the VR women indicated that they would use VR again and 22 (88%) indicated they would recommend it to a friend having ECV. There were no significant differences between groups for side effects encountered or changes in vital signs. We have shown that using VR during ECV is feasible and appears safe. Our results inform the design of future RCTs.

This study devised a dual-species biofilm model to investigate bacteria, lipoteichoic acid (LTA), and lipopolysaccharide (LPS) simultaneously, and compared the efficacy of conventional and contemporary disinfection protocols. Seventy single-rooted mandibular premolars were included. Fourteen teeth were negative control, and 56 teeth were infected with 3-week-old E. faecalis and E. coli GFP biofilm. Fourteen/56 teeth were positive control, with seven teeth processed for CLSM analysis and seven teeth sampled with paper points (PPs) and cryogenically ground for bacterial, LTA, and LPS analyses. Forty-two teeth were randomly divided into three groups: GWS (GentleWave system) + MIT (minimally invasive technique), PUI (passive ultrasonic irrigation) + CIT (conventional instrumentation technique), and XP-EF (XP-endo Finisher) + CIT (All, n = 14). Samples were collected before (s1) and after disinfection (s2) with PPs and after cryogenically ground (s3). CFUs were counted, and LTA and LPS were quantified with LTA-ELISA and LAL assay, respectively. XP-EF was as effective as PUI (p > 0.05). GWS + MIT was the most effective disinfection protocol against bacteria, LTA, and LPS (p < 0.05). In conclusion, PUI, XP-EF, and GWS were highly effective against bacteria, LTA, and LPS, with GWS being the most effective.

In order to reduce the risk of data privacy disclosure and improve the effect of information privacy protection, a differential privacy protection algorithm for network sensitive information based on singular value decomposition is proposed. TF-IDF method is used to extract network sensitive information text. By comparing the word frequency of network sensitive information, high word frequency word elements in network information content are collected to obtain the mining results of network sensitive information text. According to the decision tree theory, the equal difference privacy budget allocation mechanism is improved to achieve equal difference privacy budget allocation. By discarding some small singular values and corresponding spectral vectors, the data can be disturbed, and the availability of the original data can be retained, so that it can truly represent the original data set structure. According to the results of equal difference privacy budget allocation and singular value decomposition disturbance, the data of high-dimensional network graph is reduced by random projection, singular value decomposition is performed on the reduced data, and Gaussian noise is added to the singular value. Finally, the matrix to be published is generated through the inverse operation of singular value decomposition to achieve differential privacy protection of network sensitive information. The experimental results show that the privacy protection quality of this algorithm is high and the data availability is effectively improved.

This study aimed to evaluate the efficacy of 3 mouthwashes in reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load in the saliva of coronavirus disease 2019 (COVID-19) patients at 30 min, 1, 2 and 3 h after rinsing. This pilot study included 40 admitted COVID-19 positive patients (10 in each group). Saliva samples were collected before rinsing and at 30 min, 1, 2 and 3 h after rinsing with: Group 1-0.2% Chlorhexidine digluconate (CHX); Group 2-1.5% Hydrogen peroxide (H2O2); Group 3-Cetylpyridinium chloride (CPC) or Group 4 (control group)-No rinsing. Viral load analysis of saliva samples was assessed by Reverse Transcription quantitative PCR. Mean log10 viral load at different time points was compared to that at baseline in all groups using a random effects linear regression analysis while for comparison between groups linear regression analysis was used. The results showed that all groups had a significantly reduced mean log10 viral load both at 2 (p = 0.036) and 3 (p = 0.041) hours compared to baseline. However, there was no difference in mean log10 viral load between any of the investigated mouthwashes and the control group (non-rinsing) at the evaluated time points. Although a reduction in the SARS-CoV-2 viral load in the saliva of COVID-19 patients was observed after rinsing with mouthwashes containing 0.2% CHX, 1.5% H2O2, or CPC, the reduction detected was similar to that achieved by the control group at the investigated time points. The findings of this study may suggest that the mechanical action of rinsing/spitting results in reduction of SARS-CoV-2 salivary load.

Scientific research is driven by allocation of funding to different research projects based in part on the predicted scientific impact of the work. Data-driven algorithms can inform decision-making of scarce funding resources by identifying likely high-impact studies using bibliometrics. Compared to standardized citation-based metrics alone, we utilize a machine learning pipeline that analyzes high-dimensional relationships among a range of bibliometric features to improve the accuracy of predicting high-impact research. Random forest classification models were trained using 28 bibliometric features calculated from a dataset of 1,485,958 publications in medicine to retrospectively predict whether a publication would become high-impact. For each random forest model, the balanced accuracy score was above 0.95 and the area under the receiver operating characteristic curve was above 0.99. The high performance of high impact research prediction using our proposed models show that machine learning technologies are promising algorithms that can support funding decision-making for medical research.

Correlational evidence in non-human primates has reported increases of fronto-parietal high-beta (22-30 Hz) synchrony during the top-down allocation of visuo-spatial attention. But may inter-regional synchronization at this specific frequency band provide a causal mechanism by which top-down attentional processes facilitate conscious visual perception? To address this question, we analyzed electroencephalographic (EEG) signals from a group of healthy participants who performed a conscious visual detection task while we delivered brief (4 pulses) rhythmic (30 Hz) or random bursts of Transcranial Magnetic Stimulation (TMS) to the right Frontal Eye Field (FEF) prior to the onset of a lateralized target. We report increases of inter-regional synchronization in the high-beta band (25-35 Hz) between the electrode closest to the stimulated region (the right FEF) and right parietal EEG leads, and increases of local inter-trial coherence within the same frequency band over bilateral parietal EEG contacts, both driven by rhythmic but not random TMS patterns. Such increases were accompained by improvements of conscious visual sensitivity for left visual targets in the rhythmic but not the random TMS condition. These outcomes suggest that high-beta inter-regional synchrony can be modulated non-invasively and that high-beta oscillatory activity across the right dorsal fronto-parietal network may contribute to the facilitation of conscious visual perception. Our work supports future applications of non-invasive brain stimulation to restore impaired visually-guided behaviors by operating on top-down attentional modulatory mechanisms.

Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. Traditional machine-learning models struggle with large-scale datasets and complex relationships. This research introduces a novel methodological framework for supply chain backorder prediction, addressing the challenge of collecting large real-world datasets with 90% accuracy. Our proposed model demonstrates remarkable accuracy in predicting backorders on short and imbalanced datasets. We capture intricate patterns and dependencies by leveraging quantum-inspired techniques within the quantum-classical neural network QAmplifyNet. Experimental evaluations on a benchmark dataset establish QAmplifyNet's superiority over eight classical models, three classically stacked quantum ensembles, five quantum neural networks, and a deep reinforcement learning model. Its ability to handle short, imbalanced datasets makes it ideal for supply chain management. We evaluate seven preprocessing techniques, selecting the best one based on logistic regression's performance on each preprocessed dataset. The model's interpretability is enhanced using Explainable artificial intelligence techniques. Practical implications include improved inventory control, reduced backorders, and enhanced operational efficiency. QAmplifyNet also achieved the highest F1-score of 94% for predicting "Not Backorder" and 75% for predicting "backorder," outperforming all other models. It also exhibited the highest AUC-ROC score of 79.85%, further validating its superior predictive capabilities. QAmplifyNet seamlessly integrates into real-world supply chain management systems, empowering proactive decision-making and efficient resource allocation. Future work involves exploring additional quantum-inspired techniques, expanding the dataset, and investigating other supply chain applications. This research unlocks the potential of quantum computing in supply chain optimization and paves the way for further exploration of quantum-inspired machine learning models in supply chain management. Our framework and QAmplifyNet model offer a breakthrough approach to supply chain backorder prediction, offering superior performance and opening new avenues for leveraging quantum-inspired techniques in supply chain management.

The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially in developing countries. This study proposes to predict the risk of developing critical conditions in COVID-19 patients by training multipurpose algorithms. We followed a total of 1040 patients with a positive RT-PCR diagnosis for COVID-19 from a large hospital from São Paulo, Brazil, from March to June 2020, of which 288 (28%) presented a severe prognosis, i.e. Intensive Care Unit (ICU) admission, use of mechanical ventilation or death. We used routinely-collected laboratory, clinical and demographic data to train five machine learning algorithms (artificial neural networks, extra trees, random forests, catboost, and extreme gradient boosting). We used a random sample of 70% of patients to train the algorithms and 30% were left for performance assessment, simulating new unseen data. In order to assess if the algorithms could capture general severe prognostic patterns, each model was trained by combining two out of three outcomes to predict the other. All algorithms presented very high predictive performance (average AUROC of 0.92, sensitivity of 0.92, and specificity of 0.82). The three most important variables for the multipurpose algorithms were ratio of lymphocyte per C-reactive protein, C-reactive protein and Braden Scale. The results highlight the possibility that machine learning algorithms are able to predict unspecific negative COVID-19 outcomes from routinely-collected data.

Mother-infant interactions during the early postnatal period are critical for infant survival and the scaffolding of infant development. Rodent models are used extensively to understand how these early social experiences influence neurobiology across the lifespan. However, methods for measuring postnatal dam-pup interactions typically involve time-consuming manual scoring, vary widely between research groups, and produce low density data that limits downstream analytical applications. To address these methodological issues, we developed the Automated Maternal Behavior during Early life in Rodents (AMBER) pipeline for quantifying home-cage maternal and mother-pup interactions using open-source machine learning tools. DeepLabCut was used to track key points on rat dams (32 points) and individual pups (9 points per pup) in postnatal day 1-10 video recordings. Pose estimation models reached key point test errors of approximately 4.1-10 mm (14.39 pixels) and 3.44-7.87 mm (11.81 pixels) depending on depth of animal in the frame averaged across all key points for dam and pups respectively. Pose estimation data and human-annotated behavior labels from 38 videos were used with Simple Behavioral Analysis (SimBA) to generate behavior classifiers for dam active nursing, passive nursing, nest attendance, licking and grooming, self-directed grooming, eating, and drinking using random forest algorithms. All classifiers had excellent performance on test frames, with F1 scores above 0.886. Performance on hold-out videos remained high for nest attendance (F1 = 0.990), active nursing (F1 = 0.828), and licking and grooming (F1 = 0.766) but was lower for eating, drinking, and self-directed grooming (F1 = 0.534-0.554). A set of 242 videos was used with AMBER and produced behavior measures in the expected range from postnatal 1-10 home-cage videos. This pipeline is a major advancement in assessing home-cage dam-pup interactions in a way that reduces experimenter burden while increasing reproducibility, reliability, and detail of data for use in developmental studies without the need for special housing systems or proprietary software.