Combined application of bacteriophages with a competitive exclusion culture and carvacrol with organic acids can reduce Campylobacter in primary broiler production

For reducing Campylobacter (C.) in the food production chain and thus the risk to the consumer, the combined application of different measures as a multiple-hurdle approach is currently under discussion. This is the first study to investigate possible synergistic activities in vivo, aiming at reducing intestinal C. jejuni counts by administering (i) bacteriophages (phages) in combination with a competitive exclusion (CE) product and (ii) carvacrol combined with organic acids. The combined application of the two selected phages (Fletchervirus phage NCTC 12673 and Firehammervirus phage vB_CcM-LmqsCPL1/1) and the CE product significantly reduced C. jejuni loads by 1.0 log10 in cecal and colonic contents as well as in cloacal swabs at the end of the trial (33 and 34 days post hatch). The proportion of bacterial isolates showing reduced phage susceptibility ranged from 10.9% (isolates from cecal content) to 47.8% (isolates from cloacal swabs 32 days post hatch) for the Fletchervirus phage, while all tested isolates remained susceptible to the Firehammervirus phage. The use of carvacrol combined with an organic acid blend (sorbic acid, benzoic acid, propionic acid, and acetic acid) significantly reduced Campylobacter counts by 1.0 log10 in cloacal swabs on day 30 only.

Acute interval running induces greater excess post-exercise oxygen consumption and lipid oxidation than isocaloric continuous running in men with obesity

Studies seem to show that high-intensity interval training (HIIT) is a more time-efficient protocol for weight loss, compared with moderate-intensity continuous training (MICT). Our aim was to compare the acute effects of energy expenditure (EE) matched HIIT vs. MICT on excess post-exercise oxygen consumption (EPOC) and substrate metabolism in male college students with obesity. Twenty-one untrained male college students (age, 22 ± 3 years; body fat, 28.4 ± 4.5%) completed two acute interventions (~ 300 kcal) on a treadmill in a randomized order: (1) HIIT: 3 min bouts at 90% of maximal oxygen uptake (VO2max) with 2 min of recovery at 25% of VO2max; (2) MICT: 60% of VO2max continuous training. EPOC and substrate metabolism were measured by indirect calorimetry during and 30 min after exercise. Results showed that EPOC was higher after HIIT (66.20 ± 14.36 kcal) compared to MICT (53.91 ± 12.63 kcal, p = 0.045), especially in the first 10 min after exercise (HIIT: 45.91 ± 9.64 kcal and MICT: 34.39 ± 7.22 kcal, p = 0.041). Lipid oxidation rate was higher after HIIT (1.01 ± 0.43 mg/kg/min) compared to MICT (0.76 ± 0.46 mg/kg/min, p = 0.003). Moreover, the percentage of energy from lipid was higher after HIIT (37.94 ± 14.21%) compared to MICT (30.09 ± 13.54%, p = 0.020). We conclude that HIIT results in greater total EE and EPOC, as well as higher percentage of energy from lipid during EPOC than EE matched MICT in male college students with obesity.

Real-time near infrared artificial intelligence using scalable non-expert crowdsourcing in colorectal surgery

Surgical artificial intelligence (AI) has the potential to improve patient safety and clinical outcomes. To date, training such AI models to identify tissue anatomy requires annotations by expensive and rate-limiting surgical domain experts. Herein, we demonstrate and validate a methodology to obtain high quality surgical tissue annotations through crowdsourcing of non-experts, and real-time deployment of multimodal surgical anatomy AI model in colorectal surgery.

The agreement between jugular bulb and cerebrospinal fluid lactate levels in patients with out-of-hospital cardiac arrest

We investigated the agreement between the jugular bulb (JB) and cerebrospinal fluid (CSF) lactate levels. The study was conducted from July 2021 to June 2023 as a prospective observational cohort study at a single center. The right jugular vein was accessed, and the placement of JB catheter tip was confirmed using lateral cervical spine X-ray. A lumbar catheter was inserted between the 3rd and 4th lumbar spine of the patient. Lactate levels were measured immediately, 24 h, 48 h, and 72 h after ROSC. In patients with a good neurological prognosis, kappa between JB and CSF lactate levels measured immediately, at 24 h, 48 h, and 72 h after ROSC were 0.08, 0.36, 0.14, - 0.05 (p = 0.65, 0.06, 0.48, and 0.75, respectively). However, in patients with a poor neurological prognosis, kappa between JB and CSF lactate levels measured immediately, at 24 h, 48 h, and 72 h after ROSC were 0.38, 0.21, 0.22, 0.12 (p = 0.001, 0.04, 0.04, and 0.27, respectively). This study demonstrated that JB lactate levels exhibited significant agreement with arterial lactate levels, compared to CSF lactate levels. Therefore, this should be considered when using JB lactate to monitor cerebral metabolism.

Practical approaches in evaluating validation and biases of machine learning applied to mobile health studies

BACKGROUND

Machine learning (ML) models are evaluated in a test set to estimate model performance after deployment. The design of the test set is therefore of importance because if the data distribution after deployment differs too much, the model performance decreases. At the same time, the data often contains undetected groups. For example, multiple assessments from one user may constitute a group, which is usually the case in mHealth scenarios.

METHODS

In this work, we evaluate a model's performance using several cross-validation train-test-split approaches, in some cases deliberately ignoring the groups. By sorting the groups (in our case: Users) by time, we additionally simulate a concept drift scenario for better external validity. For this evaluation, we use 7 longitudinal mHealth datasets, all containing Ecological Momentary Assessments (EMA). Further, we compared the model performance with baseline heuristics, questioning the essential utility of a complex ML model.

RESULTS

Hidden groups in the dataset leads to overestimation of ML performance after deployment. For prediction, a user's last completed questionnaire is a reasonable heuristic for the next response, and potentially outperforms a complex ML model. Because we included 7 studies, low variance appears to be a more fundamental phenomenon of mHealth datasets.

CONCLUSIONS

The way mHealth-based data are generated by EMA leads to questions of user and assessment level and appropriate validation of ML models. Our analysis shows that further research needs to follow to obtain robust ML models. In addition, simple heuristics can be considered as an alternative for ML. Domain experts should be consulted to find potentially hidden groups in the data.

Development of sensor system and data analytic framework for non-invasive blood glucose prediction

Periodic quantification of blood glucose levels is performed using painful, invasive methods. The proposed work presents the development of a noninvasive glucose-monitoring device with two sensors, i.e., finger and wrist bands. The sensor system was designed with a near-infrared (NIR) wavelength of 940 nm emitter and a 900-1700 nm detector. This study included 101 diabetic and non-diabetic volunteers. The obtained dataset was subjected to pre-processing, exploratory data analysis (EDA), data visualization, and integration methods. Ambiguities such as the effects of skin color, ambient light, and finger pressure on the sensor were overcome in the proposed 'niGLUC-2.0v'. niGLUC-2.0v was validated with performance metrics where accuracy of 99.02%, mean absolute error (MAE) of 0.15, mean square error (MSE) of 0.22 for finger, and accuracy of 99.96%, MAE of 0.06, MSE of 0.006 for wrist prototype with ridge regression (RR) were achieved. Bland-Altman analysis was performed, where 98% of the data points were within ± 1.96 standard deviation (SD), 100% were under zone A of the Clarke Error Grid (CEG), and statistical analysis showed p < 0.05 on evaluated accuracy. Thus, niGLUC-2.0v is suitable in the medical and personal care fields for continuous real-time blood glucose monitoring.

Prevalence of chronic kidney disease and its associated factors among diabetes mellitus patients in Dessie Referral Hospital, South Wollo, Ethiopia

Diabetes mellitus shares a large proportion of kidney failure. Despite many patients suffering from diabetes mellitus and its complications in Dessie City, no study was conducted in the study area that shows the prevalence and associated factors of chronic kidney disease among diabetes mellitus patients. Therefore, this study aims to assess the prevalence of chronic kidney disease and its associated factors among adult diabetes mellitus patients attending Dessie Referral Hospital, South Wollo, Northeast Ethiopia. An institutional-based cross-sectional study was conducted at Dessie Referral Hospital among 267 randomly selected adult diabetic patients. Data were collected using questionnaires administered by interviewers. The glomerular filtration rate was estimated from serum creatinine levels. Data were entered into Epi-data version 4.6 and analyzed using SPSS version 26 software. Multi-variable logistic regression was used to determine the strength of association for the associated factors of chronic kidney disease. Variables with a p value < 0.05 were used to ascertain statistically significant associations. A total of 267 diabetic patients participated in this study. About 104 (39%) of the respondents were female and from the total, 133 (48.1%) were hypertensive. The overall prevalence of chronic kidney disease in this study was 31.5% (95% CI 25.3-37.1%). Being older (p-value = 0.003) and having hypertension (p-value = 0.043) were significant factors for chronic kidney disease among diabetes mellitus patients. This study found a high prevalence (31.5%) of chronic kidney disease among diabetic patients. Older age, having hypertension, and elevated serum creatinine were statistically significant associated factors of chronic kidney disease among patients with diabetes mellitus. Thus, clinicians should be aware of the high prevalence of chronic kidney disease in Dessie City. Moreover, emphasis should be given for old age and hypertension as contributing factors to the high prevalence in diabetic patients.

Employing supervised machine learning algorithms for classification and prediction of anemia among youth girls in Ethiopia

In developing countries, one-quarter of young women have suffered from anemia. However, the available studies in Ethiopia have been usually used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of anemia among youth girls in Ethiopia. A total of 5642 weighted samples of young girls from the 2016 Ethiopian Demographic and Health Survey dataset were utilized. The data underwent preprocessing, with 80% of the observations used for training the model and 20% for testing. Eight machine learning algorithms were employed to build and compare models. The model performance was assessed using evaluation metrics in Python software. Various data balancing techniques were applied, and the Boruta algorithm was used to select the most relevant features. Besides, association rule mining was conducted using the Apriori algorithm in R software. The random forest classifier with an AUC value of 82% outperformed in predicting anemia among all the tested classifiers. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having more than 5 family size were the top attributes to predict anemia. Association rule mining was identified the top seven best rules that most frequently associated with anemia. The random forest classifier is the best for predicting anemia. Therefore, making it potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt anemia among youth girls.

Evidence and sources of placebo effects in transcranial direct current stimulation during a single session of visuospatial working memory practice

Transcranial direct current stimulation (tDCS) can be used to non-invasively augment cognitive training. However, the benefits of tDCS may be due in part to placebo effects, which have not been well-characterized. The purpose of this study was to determine whether tDCS can have a measurable placebo effect on cognitive training and to identify potential sources of this effect. Eighty-three right-handed adults were randomly assigned to one of three groups: control (no exposure to tDCS), sham tDCS, or active tDCS. The sham and active tDCS groups were double-blinded. Each group performed 20 min of an adapted Corsi Block Tapping Task (CBTT), a visuospatial working memory task. Anodal or sham tDCS was applied during CBTT training in a right parietal-left supraorbital montage. After training, active and sham tDCS groups were surveyed on expectations about tDCS efficacy. Linear mixed effects models showed that the tDCS groups (active and sham combined) improved more on the CBTT with training than the control group, suggesting a placebo effect of tDCS. Participants' tDCS expectations were significantly related to the placebo effect, as was the belief of receiving active stimulation. This placebo effect shows that the benefits of tDCS on cognitive training can occur even in absence of active stimulation. Future tDCS studies should consider how treatment expectations may be a source of the placebo effect in tDCS research, and identify ways to potentially leverage them to maximize treatment benefit.

Hemoglobin levels are associated with retinal vascular caliber in a middle-aged birth cohort

Vascular and neural structures of the retina can be visualized non-invasively and used to predict ocular and systemic pathologies. We set out to evaluate the association of hemoglobin (Hb) levels within the national reference interval with retinal vascular caliber, optical coherence tomography (OCT) and visual field (VF) parameters in the Northern Finland 1966 Birth Cohort (n = 2319, 42.1% male, average age 47 years). The studied parameters were evaluated in Hb quintiles and multivariable linear regression models. The lowest Hb quintile of both sexes presented the narrowest central retinal vein equivalent (CRVE) and the healthiest cardiometabolic profile compared to the other Hb quintiles. In the regression models, CRVE associated positively with Hb levels in both sexes, (Bmales = 0.068 [0.001; 0.135], Bfemales = 0.087 [0.033; 0.140]), after being adjusted for key cardiometabolic and inflammatory parameters, smoking status, and fellow vessel caliber. No statistically significant associations of Hb levels with central retinal artery equivalent, OCT or VF parameters were detected. In conclusion, Hb levels were positively and specifically associated with CRVE, indicating that Hb levels are an independent factor affecting CRVE and the effect is in parallel with established risk factors for cardiometabolic diseases.

Post-stroke arrhythmia could be a potential predictor for post-stroke depression

Post-stroke depression (PSD) is regarded as the consequence of multiple contributors involving the process of cognition, mood and autonomic system, with the specific mechanism unclear yet. As a common type of stroke-heart syndromes, post-stroke arrhythmia shared some common pathogenesis with PSD. We presumed that post-stroke arrhythmia might be an early distinguishable marker for the presence of PSD and aimed to verity their association in this study. Patients with first-ever ischemic stroke were enrolled. The presence of post-stroke ectopic arrhythmia and the symptoms of arrhythmia were recorded with anti-arrhythmia drugs prescribed when necessary. Patients were followed up 3 months later to identify their presence and severity of PSD using Hamilton Depression Scale (HAMD) and also presence and severity of arrhythmia. Characteristics including the prevalence of various types of arrhythmias were compared between PSD and non-PSD groups. The HAMD scores were compared between patients with and without arrhythmia in PSD group. Logistic regression was used to identify the independent predictor of PSD. Patients with PSD had higher prevalence of post-stroke arrhythmia especially newly-detected arrhythmia, symptomatic arrhythmia and poor-controlled arrhythmia. In PSD group, patients of post-stroke arrhythmia had higher scores of HAMD than those without arrhythmia. Presence of newly-detected, symptomatic and poor-controlled arrhythmias were independent predictor of PSD. post-stroke arrhythmia especially newly-detected arrhythmia and symptomatic arrhythmia could be an early predictor of PSD. Successful control of arrhythmia was associated with reduced prevalence and severity of PSD.

Identifying characteristics and clinical conditions associated with hand grip strength in adults: the Project Baseline Health Study

Low hand grip strength (HGS) is associated with several conditions, but its value outside of the older adult population is unclear. We sought to identify the most salient factors associated with HGS from an extensive list of candidate variables while stratifying by age and sex. We used data from the initial visit from the Project Baseline Health Study (N = 2502) which captured detailed demographic, occupational, social, lifestyle, and clinical data. We applied MI-LASSO using group methods to determine variables most associated with HGS out of 175 candidate variables. We performed analyses separately for sex and age (< 65 vs. ≥ 65 years). Race was associated with HGS to varying degrees across groups. Osteoporosis and osteopenia were negatively associated with HGS in female study participants. Immune cell counts were negatively associated with HGS for male participants ≥ 65 (neutrophils) and female participants (≥ 65, monocytes; < 65, lymphocytes). Most findings were age and/or sex group-specific; few were common across all groups. Several of the variables associated with HGS in each group were novel, while others corroborate previous research. Our results support HGS as a useful indicator of a variety of clinical characteristics; however, its utility varies by age and sex.

Randomized feature selection based semi-supervised latent Dirichlet allocation for microbiome analysis

Health and disease are fundamentally influenced by microbial communities and their genes (the microbiome). An in-depth analysis of microbiome structure that enables the classification of individuals based on their health can be crucial in enhancing diagnostics and treatment strategies to improve the overall well-being of an individual. In this paper, we present a novel semi-supervised methodology known as Randomized Feature Selection based Latent Dirichlet Allocation (RFSLDA) to study the impact of the gut microbiome on a subject's health status. Since the data in our study consists of fuzzy health labels, which are self-reported, traditional supervised learning approaches may not be suitable. As a first step, based on the similarity between documents in text analysis and gut-microbiome data, we employ Latent Dirichlet Allocation (LDA), a topic modeling approach which uses microbiome counts as features to group subjects into relatively homogeneous clusters, without invoking any knowledge of observed health status (labels) of subjects. We then leverage information from the observed health status of subjects to associate these clusters with the most similar health status making it a semi-supervised approach. Finally, a feature selection technique is incorporated into the model to improve the overall classification performance. The proposed method provides a semi-supervised topic modelling approach that can help handle the high dimensionality of the microbiome data in association studies. Our experiments reveal that our semi-supervised classification algorithm is effective and efficient in terms of high classification accuracy compared to popular supervised learning approaches like SVM and multinomial logistic model. The RFSLDA framework is attractive because it (i) enhances clustering accuracy by identifying key bacteria types as indicators of health status, (ii) identifies key bacteria types within each group based on estimates of the proportion of bacteria types within the groups, and (iii) computes a measure of within-group similarity to identify highly similar subjects in terms of their health status.

A machine-learning algorithm using claims data to identify patients with homozygous familial hypercholesterolemia

Homozygous familial hypercholesterolemia (HoFH) is an underdiagnosed and undertreated ultra-rare disease. We utilized claims data from the Komodo Healthcare Map database to develop a machine-learning model to identify potential HoFH patients. We tokenized patients enrolled in MyRARE (patient support program for those prescribed evinacumab-dgnb in the United States) and linked them with their Komodo claims. A true positive HoFH cohort (n = 331) was formed by including patients from MyRARE and patients with prescriptions for evinacumab-dgnb or lomitapide. The negative cohort (n = 1423) comprised patients with or at risk for cardiovascular disease. We divided the cohort into an 80% training and 20% testing set. Overall, 10,616 candidate features were investigated; 87 were selected due to clinical relevance and importance on prediction performance. Different machine-learning algorithms were explored, with fast interpretable greedy-tree sums selected as the final machine-learning tool. This selection was based on its satisfactory performance and its easily interpretable nature. The model identified four useful features and yielded precision (positive predicted value) of 0.98, recall (sensitivity) of 0.88, area under the receiver operating characteristic curve of 0.98, and accuracy of 0.97. The model performed well in identifying HoFH patients in the testing set, providing a useful tool to facilitate HoFH screening and diagnosis via healthcare claims data.

Reverse causation between multiple sclerosis and psoriasis: a genetic correlation and Mendelian randomization study

Observational studies have found a potential bidirectional positive association between multiple sclerosis and psoriasis, but these studies are susceptible to confounding factors. We examined the directionality of causation using Mendelian randomization and estimated the genetic correlation using the linkage disequilibrium score. We performed Mendelian randomization analysis using large-scale genome-wide association studies datasets from the International Multiple Sclerosis Genetics Consortium (IMSGC, 115,803 individuals of European ancestry) and FinnGen (252,323 individuals of European ancestry). We selected several Mendelian randomization methods including causal analysis using summary effect (CAUSE), inverse variance-weighted (IVW), and pleiotropy-robust methods. According to CAUSE and IVW the genetic liability to MS reduces the risk of psoriasis (CAUSE odds ratio [OR] 0.93, p = 0.045; IVW OR 0.93, p = 2.51 × 10-20), and vice versa (CAUSE OR 0.72, p = 0.001; IVW OR 0.71, p = 4.80 × 10-26). Pleiotropy-robust methods show the same results, with all p-values < 0.05. The linkage disequilibrium score showed no genetic correlation between psoriasis and MS (rg =  - 0.071, p = 0.2852). In summary, there is genetic evidence that MS reduces the risk of psoriasis, and vice versa.

Comparative effectiveness of angioembolization versus open surgery in patients with blunt splenic injury

The effectiveness and safety of transcatheter splenic artery embolization (SAE) compared to those of open surgery in patients with blunt splenic injury (BSI) remain unclear. This retrospective cohort-matched study utilized data from the Japan Trauma Data Bank recorded between 2004 and 2019. Patients with BSI who underwent SAE or open surgery were selected. A propensity score matching analysis was used to balance the baseline covariates and compare outcomes, including all-cause in-hospital mortality and spleen salvage. From 361,706 patients recorded in the data source, this study included 2,192 patients with BSI who underwent SAE or open surgery. A propensity score matching analysis was used to extract 377 matched pairs of patients. The in-hospital mortality rates (SAE, 11.6% vs. open surgery, 11.2%, adjusted relative risk (aRR): 0.64; 95% confidence interval [CI]: 0.38-1.09, p = 0.10) were similar in both the groups. However, spleen salvage was significantly less achieved in the open surgery group than in the SAE group (SAE, 87.1% vs. open surgery, 32.1%; aRR: 2.84, 95%CI: 2.29-3.51, p < 0.001). Survival rates did not significantly differ between BSI patients undergoing SAE and those undergoing open surgery. Nonetheless, SAE was notably associated with a higher likelihood of successful spleen salvage.

Anti-inflammatory effect of thalidomide in an experimental lung donor model of brain death

Lung transplantation stands as a vital treatment for severe lung diseases, primarily sourcing organs from donors with brain death (BD). This research delved into the potential anti-inflammatory effects of thalidomide in rats with BD-induced lung complications. In this study twenty-four Wistar rats were divided into three groups: the control (CTR), brain death (BD) and brain death + thalidomide (TLD) groups. Post specific procedures, a 360 min monitoring period ensued. Comprehensive analyses of blood and heart-lung samples were conducted. Elevated IL-6 levels characterized both BD and TLD groups relative to the CTR (p = 0.0067 and p = 0.0137). Furthermore, TNF-α levels were notably higher in the BD group than both CTR and TLD (p = 0.0152 and p = 0.0495). Additionally, IL-1β concentrations were significantly pronounced in both BD and TLD compared to CTR, with the BD group surpassing TLD (p = 0.0256). Immunohistochemical assessments revealed augmented NF-ĸB expression in the BD group in comparison to both CTR and TLD (p = 0.0006 and p = 0.0005). With this study we can conclude that BD induced acute pulmonary inflammation, whereas thalidomide manifested a notable capability in diminishing key inflammatory markers, indicating its prospective therapeutic significance in lung transplantation scenarios.

Evaluation of physiological response and synchronisation errors during synchronous and pseudosynchronous stimulation trials

Rhythm perception and synchronisation is musical ability with neural basis defined as the ability to perceive rhythm in music and synchronise body movements with it. The study aimed to check the errors of synchronisation and physiological response as a reaction of the subjects to metrorhythmic stimuli of synchronous and pseudosynchronous stimulation (synchronisation with an externally controlled rhythm, but in reality controlled or produced tone by tapping) Nineteen subjects without diagnosed motor disorders participated in the study. Two tests were performed, where the electromyography signal and reaction time were recorded using the NORAXON system. In addition, physiological signals such as electrodermal activity and blood volume pulse were measured using the Empatica E4. Study 1 consisted of adapting the finger tapping test in pseudosynchrony with a given metrorhythmic stimulus with a selection of preferred, choices of decreasing and increasing tempo. Study 2 consisted of metrorhythmic synchronisation during the heel stomping test. Numerous correlations and statistically significant parameters were found between the response of the subjects with respect to their musical education, musical and sports activities. Most of the differentiating characteristics shown evidence of some group division in the undertaking of musical activities. The use of detailed analyses of synchronisation errors can contribute to the development of methods to improve the rehabilitation process of subjects with motor dysfunction, and this will contribute to the development of an expert system that considers personalised musical preferences.

Prediction of hematologic toxicity in luminal type breast cancer patients receiving neoadjuvant chemotherapy using CT L1 level skeletal muscle index

This study aims to explore the correlation between the CT-L1 and L3 body composition parameters and analyze the relationship between L1 body composition and hematologic toxicity in luminal-type breast cancer patients undergoing neoadjuvant chemotherapy. Data from 140 luminal-type breast cancer patients who underwent surgical treatment after neoadjuvant chemotherapy were analyzed retrospectively. Spearman analysis was used to assess the correlation between CT-L1 and CT-L3 body composition parameters pre-neoadjuvant chemotherapy. Additionally, univariate and multivariate logistic regression analyses were performed to identify factors influencing hematologic toxicity. CT-L1 body composition parameters were positively correlated with CT-L3 body composition parameters in 34 patients. Severe hematological toxicity occurred in 46 cases among the patient cohort. A skeletal muscle index (SMI) of < 32.91 cm2/m2, initial tumor size ≥ 3.335 cm, and a glucose-to-neutrophil ratio (GLR) ≥ 2.88 were identified as independent risk factors for severe hematologic toxicity during neoadjuvant chemotherapy in luminal-type breast cancer patients. The sample size in this study is small, and the predictive capacity of GLR in hematologic toxicity requires further research for comprehensive validation. CT-L1 analysis represents a viable alternative to CT-L3 analysis for body composition assessment. Patients with a low skeletal muscle index were more prone to experiencing severe hematologic toxicity during neoadjuvant chemotherapy.

Cas9-directed long-read sequencing to resolve optical genome mapping findings in leukemia diagnostics

Leukemias are genetically heterogeneous and diagnostics therefore includes various standard-of-care (SOC) techniques, including karyotyping, SNP-array and FISH. Optical genome mapping (OGM) may replace these as it detects different types of structural aberrations simultaneously and additionally detects much smaller aberrations (500 bp vs 5-10 Mb with karyotyping). However, its resolution may still be too low to define clinical relevance of aberrations when they are located between two OGM labels or when labels are not distinct enough. Here, we test the potential of Cas9-directed long-read sequencing (LRS) as an additional technique to resolve such potentially relevant new findings. From an internal Bionano implementation study we selected ten OGM calls that could not be validated with SOC methods. Per variant we designed crRNAs for Cas9 enrichment, prepared libraries and sequenced them on a MinION/GridION device. We could confirm all aberrations and, importantly, the actual breakpoints of the OGM calls were located between 0.2 and 5.5 kb of the OGM-estimated breakpoints, confirming the high reliability of OGM. Furthermore, we show examples of redefinition of aberrations between labels that enable judgment of clinical relevance. Our results suggest that Cas9-directed LRS can be a relevant and flexible secondary technique in diagnostic workflows including OGM.

Metabotropic glutamate receptor genetic variants and peripheral receptor expression affects trait scores of autistic probands

Glutamate (Glu) is important for memory and learning. Hence, Glu imbalance is speculated to affect autism spectrum disorder (ASD) pathophysiology. The action of Glu is mediated through receptors and we analyzed four metabotropic Glu receptors (mGluR/GRM) in Indo-Caucasoid families with ASD probands and controls. The trait scores of the ASD probands were assessed using the Childhood Autism Rating Scale2-ST. Peripheral blood was collected, genomic DNA isolated, and GRM5 rs905646, GRM6 rs762724 & rs2067011, and GRM7 rs3792452 were analyzed by PCR/RFLP or Taqman assay. Expression of mGluRs was measured in the peripheral blood by qPCR. Significantly higher frequencies of rs2067011 'A' allele/ AA' genotype were detected in the probands. rs905646 'A 'exhibited significantly higher parental transmission. Genetic variants showed independent as well as interactive effects in the probands. Receptor expression was down-regulated in the probands, especially in the presence of rs905646 'AA', rs762724 'TT', rs2067011 'GG', and rs3792452 'CC'. Trait scores were higher in the presence of rs762724 'T' and rs2067011 'G'. Therefore, in the presence of risk genetic variants, down-regulated mGluR expression may increase autistic trait scores. Since our investigation was confined to the peripheral system, in-depth exploration involving peripheral as well as central nervous systems may validate our observation.

Spatiotemporal immune atlas of a clinical-grade gene-edited pig-to-human kidney xenotransplant

Pig-to-human xenotransplantation is rapidly approaching the clinical arena; however, it is unclear which immunomodulatory regimens will effectively control human immune responses to pig xenografts. Here, we transplant a gene-edited pig kidney into a brain-dead human recipient on pharmacologic immunosuppression and study the human immune response to the xenograft using spatial transcriptomics and single-cell RNA sequencing. Human immune cells are uncommon in the porcine kidney cortex early after xenotransplantation and consist of primarily myeloid cells. Both the porcine resident macrophages and human infiltrating macrophages express genes consistent with an alternatively activated, anti-inflammatory phenotype. No significant infiltration of human B or T cells into the porcine kidney xenograft is detectable. Altogether, these findings provide proof of concept that conventional pharmacologic immunosuppression may be able to restrict infiltration of human immune cells into the xenograft early after compatible pig-to-human kidney xenotransplantation.

Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis

BACKGROUND

The field of Artificial Intelligence (AI) holds transformative potential in medicine. However, the lack of universal reporting guidelines poses challenges in ensuring the validity and reproducibility of published research studies in this field.

METHODS

Based on a systematic review of academic publications and reporting standards demanded by both international consortia and regulatory stakeholders as well as leading journals in the fields of medicine and medical informatics, 26 reporting guidelines published between 2009 and 2023 were included in this analysis. Guidelines were stratified by breadth (general or specific to medical fields), underlying consensus quality, and target research phase (preclinical, translational, clinical) and subsequently analyzed regarding the overlap and variations in guideline items.

RESULTS

AI reporting guidelines for medical research vary with respect to the quality of the underlying consensus process, breadth, and target research phase. Some guideline items such as reporting of study design and model performance recur across guidelines, whereas other items are specific to particular fields and research stages.

CONCLUSIONS

Our analysis highlights the importance of reporting guidelines in clinical AI research and underscores the need for common standards that address the identified variations and gaps in current guidelines. Overall, this comprehensive overview could help researchers and public stakeholders reinforce quality standards for increased reliability, reproducibility, clinical validity, and public trust in AI research in healthcare. This could facilitate the safe, effective, and ethical translation of AI methods into clinical applications that will ultimately improve patient outcomes.

Early life factors and oral microbial signatures define the risk of caries in a Swedish cohort of preschool children

The oral cavity harbors complex communities comprising bacteria, archaea, fungi, protozoa, and viruses. The oral microbiota is establish at birth and develops further during childhood, with early life factors such as birth mode, feeding practices, and oral hygiene, reported to influence this development and the susceptibility to caries. We here analyzed the oral bacterial composition in saliva of 260 Swedish children at two, three and five years of age using 16S rRNA gene profiling to examine its relation to environmental factors and caries development at five years of age. We were able to assign the salivary bacterial community in each child at each time point to one of seven distinct clusters. We observed an individual dynamic in the development of the oral microbiota related to early life factors, such as being first born, born by C-section, maternal perinatal antibiotics use, with a distinct transition between three and five years of age. Different bacterial signatures depending on age were related to increased caries risk, while Peptococcus consistently linked to reduced risk of caries development.

Determinants associated with low dietary diversity among migrants to Morocco: a cross sectional study

Low dietary diversity (LDD) is prevalent among vulnerable populations, posing a morbidity risk. Few studies have been conducted on the dietary diversity of migrants. The objectives of this study are to determine the prevalence of LDD among migrants in Morocco and the risk factors associated with it. In the Oriental region, we conducted a cross-sectional study with migrants between November and December 2021. The sampling method used was convenience sampling. A face-to-face, structured questionnaire was used to collect sociodemographic, behavioral, and clinical data. We calculated a dietary diversity score based on a 24-h food recall and assessed food intake. The risk factors associated with LDD were identified using multivariate logistic regression. A total of 445 migrants was enrolled. The prevalence of LDD was 31.7%. Risk factors associated with LDD were: being homeless (adjusted Odds Ratio (AOR) of 6.32; CI% [3.55-11.25]), a lack of social support (AOR of 2.30; CI% [1.33-03.98]), and low monthly income (AOR of 8.21; CI% [3.39-19.85]). Public policies must focus on social and environmental determinants. Nutrition training programs should be set up for the migrant population.

Effect of a novel mesh design and the sandblasting technique on the bond strength of computer-designed and three-dimension laser printed resin bonded bridges: an in vitro study

Resin-bonded bridges (RBBs) are a minimally invasive and aesthetically pleasing treatment modality. However, their frequent failure has posed challenges for both dental professionals and patients. This necessitates the exploration of innovative strategies to enhance the longevity of RBBs. This study aimed to assess the bond strength of a mesh bridge fabricated using computer-aided design and three-dimensional (3D) printing technology in comparison to the traditional aluminum oxide sandblasting method. A total of 48 lower incisors were embedded in acrylic bases according to a standardized computer-generated model to receive 24 metal RBBs. The two groups underwent distinct metal surface treatments: the 3D mesh novel design and sandblasting with aluminum oxide particles sized at 250.00 µm. The bond strength of the bridges was evaluated, and statistical analysis was performed using the independent samples t-test with a significance level set at α = 0.05. The findings revealed a significant difference between the two methods (p < 0.001). The 3D mesh design exhibited a mean bond strength of 387.89 ± 24.15 N, while the sandblasting technique yielded a mean value of 161.46 ± 31.25 N. In summary, the 3D mesh design substantially enhanced the bond strength of RBBs compared to the traditional sandblasting technique.

Fetal and neonatal outcomes of posterior fossa anomalies: a retrospective cohort study

The primary aim of this study was to estimate the incidence of posterior fossa anomalies (PFA) and assess the associated outcomes in King Abdulaziz Medical City (KAMC), Riyadh. All fetuses diagnosed by prenatal ultrasound with PFA from 2017 to 2021 in KAMC were analyzed retrospectively. PFA included Dandy-Walker malformation (DWM), mega cisterna magna (MCM), Blake's pouch cyst (BPC), and isolated vermian hypoplasia (VH). The 65 cases of PFA were 41.5% DWM, 46.2% MCM, 10.8% VH, and 1.5% BPC. The annual incidence rates were 2.48, 2.64, 4.41, 8.75, and 1.71 per 1000 anatomy scans for 2017, 2018, 2019, 2020, and 2021, respectively. Infants with DWM appeared to have a higher proportion of associated central nervous system (CNS) abnormalities (70.4% vs. 39.5%; p-value = 0.014) and seizures than others (45% vs. 17.9%; p-value = 0.041). Ten patients with abnormal genetic testing showed a single gene mutation causing CNS abnormalities, including a pathogenic variant in MPL, C5orf42, ISPD, PDHA1, PNPLA8, JAM3, COL18A1, and a variant of uncertain significance in the PNPLA8 gene. Our result showed that the most common PFA is DWM and MCM. The autosomal recessive pathogenic mutation is the major cause of genetic disease in Saudi patients diagnosed with PFA.

Comparison between accuracy of augmented reality computed tomography-based and portable augmented reality-based navigation systems for cup insertion in total hip arthroplasty

Augmented reality (AR) has been used for navigation during total hip arthroplasty (THA). AR computed tomography (CT)-based navigation systems and AR-based portable navigation systems that use smartphones can also be used. This study compared the accuracy of cup insertion during THA using AR-CT-based and portable AR-based navigation systems. Patients with symptomatic hip disease who underwent primary THA in the supine position using both AR CT-based and portable AR-based navigation systems simultaneously between October 2021 and July 2023 were included. The primary outcome of this study was the absolute difference between cup angles in the intraoperative navigation record and those measured on postoperative CT. The secondary outcome was to determine the factors affecting the absolute value of the navigation error in radiographic inclination (RI) and radiographic anteversion (RA) of the cup, including sex, age, body mass index, left or right side, approach, and preoperative pelvic tilt. This study included 94 consecutive patients. There were 11 men and 83 women, with a mean age of 68 years. The mean absolute errors of RI were 2.7° ± 2.0° in the AR CT-based and 3.3° ± 2.4° in the portable AR-based navigation system. The mean absolute errors of RA were 2.5° ± 2.1° in the AR CT-based navigation system and 2.3° ± 2.2° in the portable AR-based navigation system. No significant differences were observed in RI or RA of the cup between the two navigation systems (RI: p = 0.706; RA: p = 0.329). No significant factors affected the absolute value of the navigation errors in RI and RA. In conclusion, there were no differences in the accuracy of cup insertion between the AR CT-based and portable AR-based navigation systems.

Utility of accessible SARS-CoV-2 specific immunoassays in vaccinated adults with a history of advanced HIV infection

Accessible SARS-CoV-2-specific immunoassays may inform clinical management in people with HIV, particularly in case of persisting immunodysfunction. We prospectively studied their application in vaccine recipients with HIV, purposely including participants with a history of advanced HIV infection. Participants received one (n = 250), two (n = 249) or three (n = 42) doses of the BNT162b2 vaccine. Adverse events were documented through questionnaires. Sample collection occurred pre-vaccination and a median of 4 weeks post-second dose and 14 weeks post-third dose. Anti-spike and anti-nucleocapsid antibodies were measured with the Roche Elecsys chemiluminescence immunoassays. Neutralising activity was evaluated using the GenScript cPass surrogate virus neutralisation test, following validation against a Plaque Reduction Neutralization Test. T-cell reactivity was assessed with the Roche SARS-CoV-2 IFNγ release assay. Primary vaccination (2 doses) was well tolerated and elicited measurable anti-spike antibodies in 202/206 (98.0%) participants. Anti-spike titres varied widely, influenced by previous SARS-CoV-2 exposure, ethnicity, intravenous drug use, CD4 counts and HIV viremia as independent predictors. A third vaccine dose significantly boosted anti-spike and neutralising responses, reducing variability. Anti-spike titres > 15 U/mL correlated with neutralising activity in 136/144 paired samples (94.4%). Three participants with detectable anti-S antibodies did not develop cPass neutralising responses post-third dose, yet displayed SARS-CoV-2 specific IFNγ responses. SARS-CoV-2 vaccination is well-tolerated and immunogenic in adults with HIV, with responses improving post-third dose. Anti-spike antibodies serve as a reliable indicator of neutralising activity. Discordances between anti-spike and neutralising responses were accompanied by detectable IFN-γ responses, underlining the complexity of the immune response in this population.

Chemical eye injuries: a 10 year retrospective review of acute presentations and clinical outcomes in Auckland, New Zealand

To assess the aetiologies, clinical characteristics, treatment regimens, and outcomes of acute chemical injuries treated at an emergency eye clinic. Retrospective, observational study of all cases of chemical eye injury that presented acutely to the Greenlane Clinical Centre in Auckland, New Zealand from 1 January 2012 through 31 December 2021. Patient demographics, activity at the time of injury, causative chemical, clinical characteristics of injury at presentation, severity (Dua) classification, admission and discharge best corrected visual acuity (BCVA), treatment regimen, time to epithelisation and number of follow-up appointments were recorded. In total, 1522 cases involving 1919 eyes were studied. The mean age was 40.6 ± 18.8 years and 65% were male. The majority of cases occurred at home (62%) and cleaning was the most common activity (38%). There were 1490 Grade I (98%), 22 Grade II (1.5%), 5 Grade III (0.3%), 1 Grade IV (0.07%), 0 Grade V, and 4 Grade VI (0.3%) cases. An epithelial defect was noted in 409 cases (26.9%), of which re-epithelialisation occurred within one week for 378 cases (92%) and within 30 days for 384 cases (94%). Moderate vision loss (BCVA ≤ 6/12) attributed to the injury occurred in 152 (10%), while severe vision loss (BCVA ≤ 6/60) occurred in 30 (2%). Lack of irrigation at the scene was associated with an increased risk of severe injury and longstanding visual impairment (p = 0.0001). Most acute chemical injuries are mild with good clinical outcomes. Although rare, severe injuries are associated with a lack of irrigation at the scene and worse visual outcomes.

Barriers Preventing Medical Trainees from Active Participation in Research Activities

Background

Research has increasingly become important to career progression and a compulsory component in most medical programs. While medical trainees are consistently urged to undertake research endeavors, they frequently encounter obstacles at both personal and organizational levels that impede the pursuit of high-quality research. This study aims to identify the barriers and recommend successful interventions to increase research productivity amongst medical trainees.

Methods

A descriptive cross-sectional survey was carried out among interns, residents, and fellows within a single hospital located in the emirate of Abu Dhabi, UAE. The survey included inquiries regarding perceived obstacles hindering engagement in research activities, factors driving motivation for research involvement, and the assessment of how research participation relates to their job in terms of relevance.

Results

Fifty-seven medical trainees participated in the survey, reflecting a response rate of 53%. The survey highlighted common obstacles, notably including time constraints, insufficient statistical and methodology training, the weight of other educational commitments, as well as inadequate incentives and rewards. While a majority of participants expressed interest in engaging in research activities, the consensus was that more incentives and increased funding opportunities would significantly encourage their involvement.

Conclusion

Implementing successful interventions such as allocating dedicated time for research, facilitating access to research mentors, and organizing training sessions have the potential to be effective strategies in fostering a thriving research culture and subsequently elevating research productivity of medical trainees.

Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing

BACKGROUND

Patients with cancer often have unmet psychosocial needs. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This work used natural language processing to predict which patients will see a counsellor or psychiatrist from a patient's initial oncology consultation document. We believe this is the first use of artificial intelligence to predict psychiatric outcomes from non-psychiatric medical documents.

METHODS

This retrospective prognostic study used data from 47,625 patients at BC Cancer. We analyzed initial oncology consultation documents using traditional and neural language models to predict whether patients would see a counsellor or psychiatrist in the 12 months following their initial oncology consultation.

RESULTS

Here, we show our best models achieved a balanced accuracy (receiver-operating-characteristic area-under-curve) of 73.1% (0.824) for predicting seeing a psychiatrist, and 71.0% (0.784) for seeing a counsellor. Different words and phrases are important for predicting each outcome.

CONCLUSION

These results suggest natural language processing can be used to predict psychosocial needs of patients with cancer from their initial oncology consultation document. Future research could extend this work to predict the psychosocial needs of medical patients in other settings.

The evolution of robotics: research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration. Robotics has been developing since the 1960s when the first industrial robot was introduced. As technology has advanced, robotic-assisted surgery has shown numerous advantages, including more precision, efficiency, minimal invasiveness, and safety than is possible with conventional techniques, which are research hotspots and cutting-edge trends. This article reviewed the history of medical robot development and seminal research papers about current research progress. Taking the autonomous dental implant robotic system as an example, the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

Evaluation of sensitivity and specificity of Kato-Katz and circulating cathodic antigen in terms of Schistosoma japonicum using latent class analysis

Schistosoma japonicum is endemic in the Philippines. The Kato-Katz (KK) method was used to diagnose S. japonicum. This is impractical, particularly when the sample size is limited. Knowledge on point-of-care circulating cathodic antigen (CCA) test performance for S. japonicum is limited. Determining the sensitivity and specificity of new diagnostics is difficult when the gold standard test is less effective or absent. Latent class analysis (LCA) can address some limitations. A total of 484 children and 572 adults from the Philippines were screened for S. japonicum. We performed Bayesian LCA to estimate the infection prevalence, sensitivity and specificity of each test by stratifying them into two age groups. Observed prevalence assessed by KK was 50.2% and 31.8%, and by CCA was 89.9% and 66.8%, respectively. Using Bayesian LCA, among children, the sensitivity and specificity of CCA were 94.8% (88.7-99.4) and 21.5% (10.5-36.1) while those of KK were 66.0% (54.2-83.3) and 78.1% (61.1-91.3). Among adults, the sensitivity and specificity of CCA were 86.4% (76.6-96.9) and 62.8% (49.1-81.1) while those of KK were 43.6% (35.1-53.9) and 85.5% (75.8-94.6). Overall, CCA was more sensitive than KK, regardless of the age group at diagnosis, as KK was more specific. KK and CCA have different diagnostic performance, which should inform their use in the planning and implementation of S. japonicum control programs.

Concept-drifts adaptation for machine learning EEG epilepsy seizure prediction

Seizure prediction remains a challenge, with approximately 30% of patients unresponsive to conventional treatments. Addressing this issue is crucial for improving patients' quality of life, as timely intervention can mitigate the impact of seizures. In this research field, it is critical to identify the preictal interval, the transition from regular brain activity to a seizure. While previous studies have explored various Electroencephalogram (EEG) based methodologies for prediction, few have been clinically applicable. Recent studies have underlined the dynamic nature of EEG data, characterised by data changes with time, known as concept drifts, highlighting the need for automated methods to detect and adapt to these changes. In this study, we investigate the effectiveness of automatic concept drift adaptation methods in seizure prediction. Three patient-specific seizure prediction approaches with a 10-minute prediction horizon are compared: a seizure prediction algorithm incorporating a window adjustment method by optimising performance with Support Vector Machines (Backwards-Landmark Window), a seizure prediction algorithm incorporating a data-batch (seizures) selection method using a logistic regression (Seizure-batch Regression), and a seizure prediction algorithm with a dynamic integration of classifiers (Dynamic Weighted Ensemble). These methods incorporate a retraining process after each seizure and use a combination of univariate linear features and SVM classifiers. The Firing Power was used as a post-processing technique to generate alarms before seizures. These methodologies were compared with a control approach based on the typical machine learning pipeline, considering a group of 37 patients with Temporal Lobe Epilepsy from the EPILEPSIAE database. The best-performing approach (Backwards-Landmark Window) achieved results of 0.75 ± 0.33 for sensitivity and 1.03 ± 1.00 for false positive rate per hour. This new strategy performed above chance for 89% of patients with the surrogate predictor, whereas the control approach only validated 46%.

Effect of housing construction material on childhood acute respiratory infection: a hospital based case control study in Bangladesh

Despite several studies conducted to investigate housing factors, the effects of housing construction materials on childhood ARI symptoms in Bangladesh remain unclear. Hence, the study aimed to measure such a correlation among children under the age of five. A hospital-based case-control study was conducted, involving 221 cases and 221 controls from January to April 2023. Bivariate and multivariate binary logistic regression was performed to measure the degree of correlation between housing construction materials and childhood ARI symptoms. Households composed of natural floor materials had 2.7 times (95% confidence interval 1.27-5.57) and households composed of natural roof materials had 1.8 times (95% confidence interval 1.01-3.11) higher adjusted odds of having under-five children with ARI symptoms than household composed of the finished floor and finished roof materials respectively. Households with natural wall type were found protective against ARI symptoms with adjusted indoor air pollution determinants. The study indicates that poor housing construction materials are associated with an increased risk of developing ARI symptoms among under-five children in Bangladesh. National policy regarding replacing poor housing materials with concrete, increasing livelihood opportunities, and behavioral strategies programs encouraging to choice of quality housing construction materials could eliminate a fraction of the ARI burden.

Refining outcome prediction after traumatic brain injury with machine learning algorithms

Outcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3-0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.

Investigation into safflower injection as a prophylactic treatment for retinal vein occlusion in a rabbit model

The study aimed to assess the effect and mechanism of safflower injection in preventing retinal vein thrombosis in rabbits. Twenty healthy adult pigmented rabbits were randomly assigned to either the experimental group, receiving safflower injection, or the control group, receiving normal saline. After two weeks of treatment, blood samples were collected to analyze platelet adhesion and aggregation rates. Photodynamic therapy was applied to induce occlusion in the target retinal vein. Fundus photography and fluorescein angiography were recorded using a dynamic microscopic monitoring system, and laser speckle imaging was employed to assess blood flow in the affected vein. The experimental group exhibited significantly lower rates of platelet adhesion and aggregation compared to the control group. Following the induction of retinal vein occlusion, the experimental group showed a lower complete occlusion rate of the target retinal vein. Although initial blood flow in the target vein was similar between groups, the blood flow at 1, 3, and 5 min post-occlusion was significantly higher in the experimental group. Safflower injection delayed retinal vein thrombosis formation, preserved blood flow in the affected retinal area, and reduced platelet adhesion and aggregation. These effects facilitated vascular reperfusion within a limited timeframe.

Medical image fusion with deep neural networks

Medical image fusion aims to fuse multiple images from a single or multiple imaging modes to enhance their corresponding clinical applications in diagnosing and evaluating medical problems, a trend that has attracted increasing attention. However, most recent medical image fusion methods require prior knowledge, making it difficult to select image features. In this paper, we propose a novel deep medical image fusion method based on a deep convolutional neural network (DCNN) for directly learning image features from original images. Specifically, source images are first decomposed by low rank representation to obtain the principal and salient components, respectively. Following that, the deep features are extracted from the decomposed principal components via DCNN and fused by a weighted-average rule. Then, considering the complementary between the salient components obtained by the low rank representation, a simple yet effective sum rule is designed to fuse the salient components. Finally, the fused result is obtained by reconstructing the principal and salient components. The experimental results demonstrate that the proposed method outperforms several state-of-the-art medical image fusion approaches in terms of both objective indices and visual quality.

Applying the IEEE BRAIN neuroethics framework to intra-cortical brain-computer interfaces

Objective. Brain-computer interfaces (BCIs) are neuroprosthetic devices that allow for direct interaction between brains and machines. These types of neurotechnologies have recently experienced a strong drive in research and development, given, in part, that they promise to restore motor and communication abilities in individuals experiencing severe paralysis. While a rich literature analyzes the ethical, legal, and sociocultural implications (ELSCI) of these novel neurotechnologies, engineers, clinicians and BCI practitioners often do not have enough exposure to these topics.Approach. Here, we present the IEEE Neuroethics Framework, an international, multiyear, iterative initiative aimed at developing a robust, accessible set of considerations for diverse stakeholders.Main results. Using the framework, we provide practical examples of ELSCI considerations for BCI neurotechnologies. We focus on invasive technologies, and in particular, devices that are implanted intra-cortically for medical research applications.Significance. We demonstrate the utility of our framework in exposing a wide range of implications across different intra-cortical BCI technology modalities and conclude with recommendations on how to utilize this knowledge in the development and application of ethical guidelines for BCI neurotechnologies.

Microneedle combined with iontophoresis and electroporation for assisted transdermal delivery of goniothalamus macrophyllus for enhancement sonophotodynamic activated cancer therapy

The underlying study was carried out aiming at transdermal drug delivery (TDD) of Goniothalamus macrophyllus as sono-photo-sensitizer (SPS) using microneedle (MN) arrays with iontophoresis (MN-IP), electroporation (MN-EP) in conjunction with applying photodynamic therapy (PDT), sonodynamic therapy (SDT) and sono-photodynamic therapy (SPDT) as an up-to-date activated cancer treatment modality. Study was conducted on 120 male Swiss Albino mice, inoculated with Ehrlich ascites carcinoma (EAC) divided into 9 groups. We employed three different arrays of MN electrodes were used (parallel, triangular, and circular), EP, IP with different volts (6, 9, 12 V), an infrared laser and an ultrasound (pulsed and continuous wave) as our two energy sources. Results revealed that parallel 6 V TDD@MN@IP@EP can be used as effective delivery system for G. macrophyllus from skin directly to target EAC cells. In addition MN@IP@EP@TDD G. macrophyllus is a potential SPS for SPDT treatment of EAC. With respect to normal control mice and as opposed to the EAC untreated control mice, MN@EP@IP TDD G. macrophyllus in the laser, ultrasound, and combination activated groups showed a significant increase in the antioxidant markers TAC level and the GST, GR, Catalase, and SOD activities, while decrease in lipid peroxidation oxidative stress parameter MDA levels. In addition significantly increased apoptotic genes expressions (p53, caspase (3, 9), Bax, and TNF alpha) and on the other hand decreased anti- apoptotic (Bcl-2) and angiogenic (VEGF) genes expressions. Moreover significantly ameliorate liver and kidney function decreasing ALT, AST, urea and creatinine respectively. Furthermore MN@IP@EP@TDD G. macrophyllus combined with SPDT was very effective at reducing the growth of tumors and even causing cell death according to microscopic H&E stain results. This process may be related to a sono- and/or photochemical activation mechanism. According to the findings, MN@IP@EP@TDD G. macrophyllus has a lot of potential as a novel, efficient delivery method that in combination with infrared laser and ultrasound activation SPDT demonstrated promising anticancer impact for treating cancer.

Reassessing human MHC-I genetic diversity in T cell studies

The Major Histocompatibility Complex class I (MHC-I) system plays a vital role in immune responses by presenting antigens to T cells. Allele specific technologies, including recombinant MHC-I technologies, have been extensively used in T cell analyses for COVID-19 patients and are currently used in the development of immunotherapies for cancer. However, the immense diversity of MHC-I alleles presents challenges. The genetic diversity serves as the foundation of personalized medicine, yet it also poses a potential risk of exacerbating healthcare disparities based on MHC-I alleles. To assess potential biases, we analysed (pre)clinical publications focusing on COVID-19 studies and T cell receptor (TCR)-based clinical trials. Our findings reveal an underrepresentation of MHC-I alleles associated with Asian, Australian, and African descent. Ensuring diverse representation is vital for advancing personalized medicine and global healthcare equity, transcending genetic diversity. Addressing this disparity is essential to unlock the full potential of T cells for enhancing diagnosis and treatment across all individuals.

Effect of a fixed combination of ripasudil and brimonidine on aqueous humor dynamics in mice

Ripasudil-brimonidine fixed-dose combination (K-232) simultaneously targets three different intraocular pressure (IOP) lowering mechanisms, increasing trabecular meshwork outflow and uveoscleral outflow, and reducing aqueous humor production Vascularly, ripasudil induces transient vasodilation, brimonidine transient vasoconstriction. Investigating effects on IOP, aqueous dynamics, and EVP in mice eyes by microneedle and constant-pressure perfusion methods, and on cytoskeletal and fibrotic proteins changes in HTM cells by a gel contraction assay and immunocytochemistry. Ripasudil, K-232, and brimonidine droplets significantly reduced IOP at 30 min, with K-232 sustaining the effect at 60 min. For EVP, only K-232 exhibited reduced EVP until 60 min after instillation. In vitro, ripasudil inhibited gel contractility and TGFβ2-induced fibrotic changes, whereas brimonidine did not. K-232 significantly lowered IOPs in mice by combining the effects of ripasudil and brimonidine. Brimonidine alone also showed IOP reductions with enhanced outflow facility, and the drug did not interfere with the effects of ripasudil on the trabecular meshwork outflow; K-232 and ripasudil alone both significantly lowered the EVP and enhanced outflow facility, demonstrating that K-232 efficiently reduces IOPs.

Association between self-reported METs and other perioperative cardiorespiratory fitness assessment tools in abdominal surgery-a prospective cross-sectional correlation study

Cardiovascular complications represent a significant proportion of adverse events during the perioperative period, necessitating accurate preoperative risk assessment. This study aimed to investigate the association between well-established risk assessment tools and self-reported preoperative physical performance, quantified by metabolic equivalent (MET) equivalents, in high-risk patients scheduled for elective abdominal surgery. A prospective cross-sectional correlation study was conducted, involving 184 patients admitted to a Gastrointestinal Surgery Department. Various risk assessment tools, including the Revised Cardiac Risk Index (RCRI), Surgical Mortality Probability Model (S-MPM), American University of Beirut (AUB)-HAS2 Cardiovascular Risk Index, and Surgical Risk Calculator (NSQIP-MICA), were utilized to evaluate perioperative risk. Patients self-reported their physical performance using the MET-REPAIR questionnaire. The findings demonstrated weak or negligible correlations between the risk assessment tools and self-reported MET equivalents (Spearman's ρ = - 0.1 to - 0.3). However, a statistically significant relationship was observed between the ability to ascend two flights of stairs and the risk assessment scores. Good correlations were identified among ASA-PS, S-MPM, NSQIP-MICA, and AUB-HAS2 scores (Spearman's ρ = 0.3-0.8). Although risk assessment tools exhibited limited correlation with self-reported MET equivalents, simple questions regarding physical fitness, such as the ability to climb stairs, showed better associations. A comprehensive preoperative risk assessment should incorporate both objective and subjective measures to enhance accuracy. Further research with larger cohorts is needed to validate these findings and develop a comprehensive screening tool for high-risk patients undergoing elective abdominal surgery.

Nobiletin alleviates cisplatin-induced ototoxicity via activating autophagy and inhibiting NRF2/GPX4-mediated ferroptosis

Nobiletin, a citrus polymethoxy flavonoid with antiapoptotic and antioxidative properties, could safeguard against cisplatin-induced nephrotoxicity and neurotoxicity. Cisplatin, as the pioneer of anti-cancer drug, the severe ototoxicity limits its clinical applications, while the effect of nobiletin on cisplatin-induced ototoxicity has not been identified. The current study investigated the alleviating effect of nobiletin on cisplatin-induced ototoxicity and the underlying mechanisms. Apoptosis and ROS formation were evaluated using the CCK-8 assay, Western blotting, and immunofluorescence, indicating that nobiletin attenuated cisplatin-induced apoptosis and oxidative stress. LC3B and SQSTM1/p62 were determined by Western blotting, qPCR, and immunofluorescence, indicating that nobiletin significantly activated autophagy. Nobiletin promoted the nuclear translocation of NRF2 and the transcription of its target genes, including Hmox1, Nqo1, and ferroptosis markers (Gpx4, Slc7a11, Fth, and Ftl), thereby inhibiting ferroptosis. Furthermore, RNA sequencing analysis verified that autophagy, ferroptosis, and the NRF2 signaling pathway served as crucial points for the protection of nobiletin against ototoxicity caused by cisplatin. Collectively, these results indicated, for the first time, that nobiletin alleviated cisplatin-elicited ototoxicity through suppressing apoptosis and oxidative stress, which were attributed to the activation of autophagy and the inhibition of NRF2/GPX4-mediated ferroptosis. Our study suggested that nobiletin could be a prospective agent for preventing cisplatin-induced hearing loss.

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules

Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporting of thyroid ultrasound results. Within TI-RADS, a category 4 designation signifies a thyroid nodule with an intermediate level of suspicion for malignancy. Accurate classification of these nodules is crucial for proper management, as it can potentially reduce unnecessary surgeries and improve patient outcomes. This study utilized deep learning techniques to effectively classify TI-RADS category 4 thyroid nodules as either benign or malignant. A total of 500 patients were included in the study and randomly divided into a training group (350 patients) and a test group (150 patients). The YOLOv3 model was constructed and evaluated using various metrics, achieving an 84% accuracy in the classification of TI-RADS category 4 thyroid nodules. Based on the predictions of the model, along with clinical and ultrasound data, a nomogram was developed. The performance of the nomogram was superior in both the training and testing groups. Furthermore, the calibration curve demonstrated good agreement between predicted probabilities and actual outcomes. Decision curve analysis further confirmed that the nomogram provided greater net benefits. Ultimately, the YOLOv3 model and nomogram successfully improved the accuracy of distinguishing between benign and malignant TI-RADS category 4 thyroid nodules, which is crucial for proper management and improved patient outcomes.

Risk of post-operative bleeding after dentoalveolar surgery in patients taking anticoagulants: a cohort study using the common data model

This retrospective study aimed to determine risk factors associated with post-operative bleeding after dentoalveolar surgery in patients taking anticoagulants. Patients taking anticoagulants who were planned to undergo periodontal flap operation, tooth extraction or implant surgery were included. Patients were divided into two subgroups according to the maintenance of anticoagulants following medical consultation: (1) maintenance group and (2) discontinuation group. The analysed patient-related factors included systemic diseases, maintenance of anticoagulants and types of anticoagulant. Intra- and post-operative treatment-related factors, haemostatic methods and post-operative bleeding were collected for statistical analyses. There were 35 post-operative bleeding complications (6.5%) in the 537 included patients: 21 (8.6%) in maintenance group and 14 (4.8%) in discontinuation group. The type of anticoagulant (p = 0.037), tooth extraction combined with bone grafting (p = 0.016) and type of implant surgery (p = 0.032) were significantly related to the post-operative bleeding rate. In the maintenance group, atrial fibrillation [odds ratio (OR) = 6.051] and vitamin K inhibitors (OR = 3.679) were associated with a significantly higher bleeding risk. From this result, it can be inferred that the decision to continue anticoagulants should be made carefully based on the types of anticoagulant and the characteristics of dentoalveolar surgeries performed: extraction with bone grafting, multiple implantations and involvement of maxillary arch.