Non-line-of-sight optical wireless communication system enabled by wavefront shaping for multi-user indoor access.

In this Letter, we experimentally investigate a non-line-of-sight (NLOS) optical wireless communication (OWC) system that utilizes wavefront shaping techniques to realize simultaneous data transmission for multiple users. Wavefront shaping techniques are employed to address the issue of low intensity of diffusely reflected light at the receiver in NLOS scenarios for indoor high-speed access. To achieve communication path planning and tracing for two different users in free-space optical communication, the pixels of the spatial light modulator (SLM) are divided into two halves to separately manipulate the wavefront of two independent data carriers centered at different wavelengths. The maximum received optical power can be effectively improved by more than 15 dB with the wavefront shaping technique. To avoid power enhancement of non-target wavelength, the wavelength difference of two different users is experimentally studied. The difference in power enhancement ratio (DPER) is increased with the wavelength difference, and 14.95 dB DPER is obtained with a 10 nm wavelength difference. Under the aforementioned wavelength planning strategy, successful transmission and reception of 2 × 160 Gbit/s 16-QAM signals for two users with coherent detection is achieved using wavelengths of 1550 and 1560 nm in an indoor access scenario.

Development and Validation of a Clinical Model for Predicting Delay in Postoperative Transfer Out of the Post-Anesthesia Care Unit: A Retrospective Cohort Study.

Objective: We aimed to analyze the factors related to delay in transfer of patients in the post-anesthesia care unit (PACU) and to develop and validate a prediction model for understanding these factors to guide precise clinical intervention. Methods: We collected data from two cohorts of 1153 and 297 patients who underwent surgery and were treated in the PACU at two time points. We examined their clinical features and anesthesia care data using analytical methods such as logistic regression, Random Forest, and eXtreme Gradient Boosting (Xgboost) to screen out variables and establish a prediction model. We then validated and simplified the model and plotted a nomogram. Using LASSO regression, we reduced the dimensionality of the data. We developed multiple models and plotted receiver operating characteristic (ROC) and calibration curves. We then constructed a simplified model by pooling the identified variables, which included hemoglobin (HB), alanine transaminase (ALT), glucose levels, duration of anesthesia, and the minimum bispectral index value (BIS_min). Results: The model had good prediction performance parameters in the training and validation sets, with an AUC of 0.909 (0.887-0.932) in the training set and 0.939 (0.919-0.959) in the validation set. When we compared model 6 with other models, the net reclassification index (NRI) and the integrated discriminant improvement (IDI) index indicated that it did not differ significantly from the other models. We developed a scoring system, and it showed good prediction performance when verified with the training and validation sets as well as external data. Additionally, both the decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated the potential clinical efficacy of the model in guiding patient interventions. Conclusion: Predicting transfer delays in the post-anesthesia care unit using predictive models is feasible; however, this merits further exploration.

Clinical effects of traditional Chinese herbal medicine management in patients with COVID-19 sequelae: A hospital-based retrospective cohort study in Taiwan.

Introduction: An estimated 43% of COVID-19 patients showed sequelae, including fatigue, neurocognitive impairment, respiratory symptoms, and smell or taste disorders. These sequelae significantly affect an individual's health, work capacity, healthcare systems, and socioeconomic aspects. Traditional Chinese herbal medicine (TCHM) management showed clinical benefits in treating patients with COVID-19 sequelae. This study aimed to analyze the effects of personalized TCHM management in patients with COVID-19 sequelae. Methods: After the COVID-19 outbreak in Taiwan, we recorded Chronic Obstructive Pulmonary Disease Assessment Tool (CAT), Chalder Fatigue Questionnaire (CFQ-11), and Brief Symptom Rating Scale (BSRS-5) to assess post-COVID respiratory, fatigue, and emotional distress symptoms, respectively. In this study, we retrospectively reviewed the medical records between July 2022 and March 2023. We analyzed the effects of TCHM administration after 14- and 28-days of treatment. Results: 47 patients were included in this study. The results demonstrated that personalized TCHM treatment significantly improved the CAT, CFQ-11, and BSRS-5 scores after 14 and 28 days. TCHM alleviated physical and psychological fatigue. In logistic regression analysis, there was no statistically significant differences in the severity of the baseline symptoms and TCHM administration effects concerning the duration since the initial confirmation of COVID-19, sex, age, or dietary preference (non-vegetarian or vegetarian). Conclusions: Our study suggested that personalized TCHM treatment notably reduced fatigue, respiratory and emotional distress symptoms after 14- and 28-days of treatment in patients with COVID-19 sequelae. We propose that TCHM should be considered as an effective intervention for patients with COVID-19 sequelae.

High fidelity detection of miRNAs from complex physiological samples through electrochemical nanosensors empowered by proximity catalysis and magnetic separation.

Electrochemical detection of miRNA biomarkers in complex physiological samples holds great promise for accurate evaluation of tumor burden in the perioperative period, yet limited by reproducibility and bias issues. Here, nanosensors installed with hybrid probes that responsively release catalytic DNAzymes (G-quadruplexes/hemin) were developed to solve the fidelity challenge in an immobilization-free detection. miRNA targets triggered toehold-mediated strand displacement reactions on the sensor surface and resulted in amplified shedding of DNAzymes. Subsequently, the interference background was removed by Fe3O4 core-facilitated magnetic separation. Binding aptamers of the electrochemical reporter (dopamine) were tethered closely to the catalytic units for boosting H2O2-mediated oxidation through proximity catalysis. The one-to-many conversion by dual amplification from biological-chemical catalysis facilitated sufficient homogeneous sensing signals on electrodes. Thereby, the nanosensor exhibited a low detection limit (2.08 fM), and high reproducibility (relative standard deviation of 1.99%). Most importantly, smaller variations (RSD of 0.51-1.04%) of quantified miRNAs were observed for detection from cell lysates, multiplexed detection from unprocessed serum, and successful discrimination of small upregulations in lysates of tumor tissue samples. The nanosensor showed superior diagnostic performance with an area under curve (AUC) of 0.97 and 94% accuracy in classifying breast cancer patients and healthy donors. These findings demonstrated the synergy of signal amplification and interference removal in achieving high-fidelity miRNA detection for practical clinical applications.

Demystifying estimands in cluster-randomised trials.

Estimands can help clarify the interpretation of treatment effects and ensure that estimators are aligned with the study's objectives. Cluster-randomised trials require additional attributes to be defined within the estimand compared to individually randomised trials, including whether treatment effects are marginal or cluster-specific, and whether they are participant- or cluster-average. In this paper, we provide formal definitions of estimands encompassing both these attributes using potential outcomes notation and describe differences between them. We then provide an overview of estimators for each estimand, describe their assumptions, and show consistency (i.e. asymptotically unbiased estimation) for a series of analyses based on cluster-level summaries. Then, through a re-analysis of a published cluster-randomised trial, we demonstrate that the choice of both estimand and estimator can affect interpretation. For instance, the estimated odds ratio ranged from 1.38 (p = 0.17) to 1.83 (p = 0.03) depending on the target estimand, and for some estimands, the choice of estimator affected the conclusions by leading to smaller treatment effect estimates. We conclude that careful specification of the estimand, along with an appropriate choice of estimator, is essential to ensuring that cluster-randomised trials address the right question.

Ultrasound-targeted microbubble destruction improves the suppression and magnetic resonance imaging of pancreatic cancer with polyethyleneimine nanogels.

The chemoresistance of pancreatic cancer tumors urgently needs to be addressed. Pancreatic cancer is characterized by an abundant stroma, with significant fibrous connective tissue formation that encapsulates the tumor parenchyma and forms an interstitial microenvironment. Pancreatic stellate cells (PSCs) play a crucial role in this microenvironment and specially secrete periosteal protein (periostin), which can promote tumor growth, metastasis, and chemoresistance. Therefore, periostin has become a specific target of chemotherapy resistance intervention methods. The proposed polyethyleneimine (PEI) nanogels have multiple modification and efficient drug-loading properties. Additionally, ultrasound-targeted microbubble destruction (UTMD) supports the breakdown of the tough interstitial barrier of pancreatic cancer. A small interfering RNA (siRNA) can be used to downregulated the periostin gene, while sustained release of gemcitabine can promote killing of tumor cells. This method achieves a combination of gene silencing and chemotherapy. The imaging effect can be evaluated using magnetic resonance imaging (MRI). The ultimate goal of this work is to support individualized and effective therapeutic methods and help develop new strategies for pancreatic cancer treatment.

Rationale and Design of a Phase 2, Double-blind, Placebo-Controlled, Randomized Trial Evaluating AMP Kinase-Activation by Metformin in Focal Segmental Glomerulosclerosis.

Introduction: Focal segmental glomerulosclerosis (FSGS), the most common primary glomerular disease leading to end-stage kidney disease (ESKD), is characterized by podocyte injury and depletion, whereas minimal change disease (MCD) has better outcomes despite podocyte injury. Identifying mechanisms capable of preventing podocytopenia during injury could transform FSGS to an "MCD-like" state. Preclinical data have reported conversion of an MCD-like injury to one with podocytopenia and FSGS by inhibition of AMP-kinase (AMPK) in podocytes. Conversely, in FSGS, AMPK-activation using metformin (MF) mitigated podocytopenia and azotemia. Observational studies also support beneficial effects of MF on proteinuria and chronic kidney disease (CKD) outcomes in diabetes. A randomized controlled trial (RCT) to test MF in podocyte injury with FSGS has not yet been conducted. Methods: We report the rationale and design of phase 2, double-blind, placebo-controlled RCT evaluating the efficacy and safety of MF as adjunctive therapy in FSGS. By randomizing 30 patients with biopsy-confirmed FSGS to MF or placebo (along with standard immunosuppression), we will study mechanistic biomarkers that correlate with podocyte injury or depletion and evaluate outcomes after 6 months. We specifically integrate novel urine, blood, and tissue markers as surrogates for FSGS progression along with unbiased profiling strategies. Results and Conclusion: Our phase 2 trial will provide insight into the potential efficacy and safety of MF as adjunctive therapy in FSGS-a crucial step to developing a larger phase 3 study. The mechanistic assays here will guide the design of other FSGS trials and contribute to understanding AMPK activation as a potential therapeutic target in FSGS. By repurposing an inexpensive agent, our results will have implications for FSGS treatment in resource-poor settings.

Multidisciplinary comprehensive treatment of massive hepatocellular carcinoma with hemorrhage: A case report and review of literature.

BACKGROUND: Hepatocellular carcinoma (HCC), a major contributor to cancer-related deaths, is particularly prevalent in Asia, largely due to hepatitis B virus infection. Its prognosis is generally poor. This case report contributes to the medical literature by detailing a unique approach in treating a large HCC through multidisciplinary collaboration, particularly in patients with massive HCC complicated by ruptured bleeding, a scenario not extensively documented previously. CASE SUMMARY: The patient presented with large HCC complicated by intratumoral bleeding. Treatment involved a multidisciplinary approach, providing individualized care. The strategy included drug-eluting bead transarterial chemoembolization, sorafenib-targeted therapy, laparoscopic partial hepatectomy, and standardized sintilimab monoclonal antibody therapy. Six months after treatment, the patient achieved complete radiological remission, with significant symptom relief. Imaging studies showed no lesions or recurrence, and clinical assessments confirmed complete remission. This report is notable as possibly the first documented case of successfully treating such complex HCC conditions through integrated multidisciplinary efforts, offering new insights and a reference for future similar cases. CONCLUSION: This study demonstrated effective multidisciplinary treatment for massive HCC with intratumoral bleeding, providing insights for future similar cases.

Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs.

The cluster randomized crossover design has been proposed to improve efficiency over the traditional parallel-arm cluster randomized design. While statistical methods have been developed for designing cluster randomized crossover trials, they have exclusively focused on testing the overall average treatment effect, with little attention to differential treatment effects across subpopulations. Recently, interest has grown in understanding whether treatment effects may vary across pre-specified patient subpopulations, such as those defined by demographic or clinical characteristics. In this article, we consider the two-treatment two-period cluster randomized crossover design under either a cross-sectional or closed-cohort sampling scheme, where it is of interest to detect the heterogeneity of treatment effect via an interaction test. Assuming a patterned correlation structure for both the covariate and the outcome, we derive new sample size formulas for testing the heterogeneity of treatment effect with continuous outcomes based on linear mixed models. Our formulas also address unequal cluster sizes and therefore allow us to analytically assess the impact of unequal cluster sizes on the power of the interaction test in cluster randomized crossover designs. We conduct simulations to confirm the accuracy of the proposed methods, and illustrate their application in two real cluster randomized crossover trials.

Oxidative balance score: a potential tool for reducing the risk of colorectal cancer and its subsites incidences.

Background: The Oxidative Balance Score (OBS) is commonly used to assess oxidative stress and provides a comprehensive evaluation of dietary and lifestyle-related exposures. However, there is limited research on the association between OBS and colorectal cancer (CRC), its subsites, and complications. The objective of this study was to assess the relationship between OBS and the risk of CRC, its subsites, and common complications in a large prospective cohort study. Methods: We included data from 175,808 participants in the UK Biobank data sample repository from 2006 to 2010. We evaluated OBS using a scoring system based on 22 dietary and lifestyle factors. Multiple adjustments, including multivariate Cox proportional hazard regression, gender stratification, subgroup analysis, and sensitivity analysis, were performed to fully explore the relationship between OBS and CRC, its subsites, and complications. The mediation analysis was conducted to investigate whether serum albumin, uric acid, and neutrophil levels mediate the relationship between OBS and CRC. Results: After adjusting for potential confounding factors, a significant negative correlation was found between OBS and the risk of CRC and its subsites (proximal colon cancer, distal colon cancer, and rectal cancer). This correlation was particularly pronounced in male CRC patients. Serum albumin, uric acid, and neutrophil count, which are biomarkers, were found to have a significant mediating effect between OBS and CRC. Conclusion: Our study suggests that higher exposure to antioxidants assessed through OBS (diet and lifestyle rich in antioxidants) may decrease the occurrence of CRC and its subsites.

The impact of spiritual care on the psychological health and quality of life of adults with heart failure: a systematic review of randomized trials.

Background: Heart failure (HF) brings not only physical pain but also psychological distress. This systematic review investigated the influence of spiritual care on the psychological well-being and quality of life in adults with HF. Methods: We conducted a systematic literature review following PRISMA guidelines, searching seven electronic databases for relevant randomized controlled studies without language or temporal restrictions. The studies were assessed for quality using the Cochrane Bias Risk tool. Results: A total of 13 studies (882 participants) were reviewed, investigating interventions such as religion, meditation, mental health, cognitive interventions, and spiritual support. Key factors influencing the effectiveness of spiritual care implementation included integration into routine care, respect for diversity, patient engagement, intervention quality, and alignment with patient beliefs. The majority of the studies indicated that spiritual care has a potentially beneficial impact on the mental health and quality of life of patients with HF. Conclusion: The findings provide valuable insights for healthcare professionals, highlighting the importance of adopting a spiritual care approach to healthcare for this population.

PD-L1 knockdown suppresses vasculogenic mimicry of non-small cell lung cancer by modulating ZEB1-triggered EMT.

BACKGROUND: PD-L1 overexpression is commonly observed in various malignancies and is strongly correlated with poor prognoses for cancer patients. Moreover, PD-L1 has been shown to play a significant role in promoting angiogenesis and epithelial-mesenchymal transition (EMT) processes across different cancer types. METHODS: The relationship between PD-L1 and vasculogenic mimicry as well as epithelial-mesenchymal transition (EMT) was explored by bioinformatics approach and immunohistochemistry. The functions of PD-L1 in regulating the expression of ZEB1 and the EMT process were assessed by Western blotting and q-PCR assays. The impact of PD-L1 on the migratory and proliferative capabilities of A549 and H1299 cells was evaluated through wound healing, cell invasion, and CCK8 assays following siRNA-mediated PD-L1 knockdown. Tube formation assay was utilized to evaluate the presence of VM structures. RESULTS: In this study, increased PD-L1 expression was observed in A549 and H1299 cells compared to normal lung epithelial cells. Immunohistochemical analysis revealed a higher prevalence of VM structures in the PD-L1-positive group compared to the PD-L1-negative group. Additionally, high PD-L1 expression was also found to be significantly associated with advanced TNM stage and increased metastasis. Following PD-L1 knockdown, NSCLC cells exhibited a notable reduction in their ability to form tube-like structures. Moreover, the levels of key EMT and VM-related markers, including N-cadherin, MMP9, VE-cadherin, and VEGFA, were significantly decreased, while E-cadherin expression was upregulated. In addition, the migration and proliferation capacities of both cell lines were significantly inhibited after PD-L1 or ZEB1 knockdown. CONCLUSIONS: Knockdown PD-L1 can inhibit ZEB1-mediated EMT, thereby hindering the formation of VM in NSCLC.

Simplified Assessment of Radioiodine Biokinetics for Thyroid Cancer Patients: A Practical Approach Using Continuous External Radiation Monitoring.

INTRODUCTION: The biokinetics of radioiodine (RAI) in thyroid cancer patients are complex. This study aims to develop a practical approach for assessing RAI biokinetics to predict patient discharge time and estimate radiation exposure to caregivers. METHODS: We retrospectively reviewed data from patients with differentiated thyroid carcinoma undergoing RAI treatment. Serial radiation dose rates were dynamically collected during hospitalization and fitted to a biexponential model to assess the biokinetic features: RAI uptake fraction of thyroid tissue (Ft) and effective half-life of extra-thyroid tissue (Tet). Correlations with 99mTc thyroid uptake ratio (TcUR), radiation retention ratio (RR), renal function, and body mass index (BMI) were analyzed. RESULTS: Thirty-five patients were enrolled. The derived Ft was 0.08 ± 0.06 and Tet was 7.57 ± 1.45 h. Pearson's correlation analysis revealed a significant association between Ft and both TcUR and RR (p < 0.05), while Tet correlated with renal function and BMI (p < 0.05). CONCLUSION: This novel and practical method assessing RAI biokinetics demonstrates consistency with other parameters and related studies, enhancing the model reliability. It shows promise in predicting an appropriate discharge time and estimating radiation exposure to caregivers, allowing for modifications to radiation protection precautions to follow ALARA principle and minimize the potential risks from radiation exposure.

The Role of Place Attachment in the Relationship between Attitudes toward Aging and Subjective Well-Being among Community-Dwelling Older Adults in Taiwan.

Subjective well-being presents a societal challenge for vulnerable older adults. This study aims to investigate the mediating role of place attachment in the relationship between attitudes toward aging and subjective well-being among community-dwelling older adults in Taiwan. Two waves of investigations were conducted to examine the interplay between attitudes toward aging, subjective well-being, and place attachment among older adults. In Wave I, 1190 participants were enrolled, revealing predominantly younger cohorts with substantial educational levels. The subsequent Wave II involved 483 participants, maintaining continuity in characteristics. Subjective well-being remained moderate across waves, with prevalent positive attitudes toward aging. Place attachment scores indicated moderate to high associations. After controlling for demographics, structural equation modeling (SEM) in both waves revealed significant positive associations: attitudes toward aging influenced well-being, attitudes toward aging were positively associated with place attachment, and place attachment was positively related to well-being. Mediation testing confirmed the mediating role of place attachment in the relationship between attitudes toward aging and well-being. These findings underscore the important role of place attachment. It is evident that improving attitudes toward aging is an effective intervention which can lead to a better sense of well-being by enhancing place attachment to empower civil society.

Exploring the frontiers of therapeutic breadth of antifungal peptides: A new avenue in antifungal drugs.

The growing prevalence of fungal infections alongside rising resistance to antifungal drugs poses a significant challenge to public health safety. At the close of the 2000s, major pharmaceutical firms began to scale back on antimicrobial research due to repeated setbacks and diminished economic gains, leaving only smaller companies and research labs to pursue new antifungal solutions. Among various natural sources explored for novel antifungal compounds, antifungal peptides (AFPs) emerge as particularly promising. Despite their potential, AFPs receive less focus than their antibacterial counterparts. These peptides have been sourced extensively from nature, including plants, animals, insects, and especially bacteria and fungi. Furthermore, with advancements in recombinant biotechnology and computational biology, AFPs can also be synthesized in lab settings, facilitating peptide production. AFPs are noted for their wide-ranging efficacy, in vitro and in vivo safety, and ability to combat biofilms. They are distinguished by their high specificity, minimal toxicity to cells, and reduced likelihood of resistance development. This review aims to comprehensively cover AFPs, including their sources-both natural and synthetic-their antifungal and biofilm-fighting capabilities in laboratory and real-world settings, their action mechanisms, and the current status of AFP research. ONE-SENTENCE SUMMARY: This comprehensive review of AFPs will be helpful for further research in antifungal research.

Prospective study of AI-assisted prediction of breast malignancies in physical health examinations: role of off-the-shelf AI software and comparison to radiologist performance.

Objective: In physical health examinations, breast sonography is a commonly used imaging method, but it can lead to repeated exams and unnecessary biopsy due to discrepancies among radiologists and health centers. This study explores the role of off-the-shelf artificial intelligence (AI) software in assisting radiologists to classify incidentally found breast masses in two health centers. Methods: Female patients undergoing breast ultrasound examinations with incidentally discovered breast masses were categorized according to the 5th edition of the Breast Imaging Reporting and Data System (BI-RADS), with categories 3 to 5 included in this study. The examinations were conducted at two municipal health centers from May 2021 to May 2023.The final pathological results from surgical resection or biopsy served as the gold standard for comparison. Ultrasonographic images were obtained in longitudinal and transverse sections, and two junior radiologists and one senior radiologist independently assessed the images without knowing the pathological findings. The BI-RADS classification was adjusted following AI assistance, and diagnostic performance was compared using receiver operating characteristic curves. Results: A total of 196 patients with 202 breast masses were included in the study, with pathological results confirming 107 benign and 95 malignant masses. The receiver operating characteristic curve showed that experienced breast radiologists had higher diagnostic performance in BI-RADS classification than junior radiologists, similar to AI classification (AUC = 0.936, 0.806, 0.896, and 0.950, p < 0.05). The AI software improved the accuracy, sensitivity, and negative predictive value of the adjusted BI-RADS classification for the junior radiologists' group (p< 0.05), while no difference was observed in the senior radiologist group. Furthermore, AI increased the negative predictive value for BI-RADS 4a masses and the positive predictive value for 4b masses among radiologists (p < 0.05). AI enhances the sensitivity of invasive breast cancer detection more effectively than ductal carcinoma in situ and rare subtypes of breast cancer. Conclusions: The AI software enhances diagnostic efficiency for breast masses, reducing the performance gap between junior and senior radiologists, particularly for BI-RADS 4a and 4b masses. This improvement reduces unnecessary repeat examinations and biopsies, optimizing medical resource utilization and enhancing overall diagnostic effectiveness.

Subtype prediction of intrahepatic cholangiocarcinoma using dynamic contrast-enhanced ultrasound.

OBJECTIVE: The study aimed to investigate the predictive value of dynamic contrast-enhanced ultrasound (DCE-US) in differentiating small-duct (SD) and large-duct (LD) types of intrahepatic cholangiocarcinoma (ICC). METHODS: This study retrospectively enrolled 110 patients with pathologically confirmed ICC lesions who were subject to preoperative contrast-enhanced ultrasound (CEUS) examinations between January 2022 and February 2023. Patients were further classified according to the subtype: SD-type and LD-type, and an optimal predictive model was established and validated using the above pilot cohort. The test cohort, consisting of 48 patients prospectively enrolled from March 2023 to September 2023, was evaluated. RESULTS: In the pilot cohort, compared with SD-type ICCs, more LD-type ICCs showed elevated carcinoembryonic antigen (p < 0.001), carbohydrate antigen 19-9 (p = 0.004), ill-defined margin (p = 0.018), intrahepatic bile duct dilation (p < 0.001). Among DCE-US quantitative parameters, the wash-out area under the curve (WoAUC), wash-in and wash-out area under the curve (WiWoAUC), and fall time (FT) at the margin of lesions were higher in the SD-type group (all p < 0.05). Meanwhile, the mean transit time (mTT) and wash-out rate (WoR) at the margin of the lesion were higher in the LD-type group (p = 0.041 and 0.007, respectively). Logistic regression analysis showed that intrahepatic bile duct dilation, mTT, and WoR were significant predictive factors for predicting ICC subtypes, and the AUC of the predictive model achieved 0.833 in the test cohort. CONCLUSIONS: Preoperative DCE-US has the potential to become a novel complementary method for predicting the pathological subtype of ICC. CRITICAL RELEVANCE STATEMENT: DCE-US has the potential to assess the subtypes of ICC lesions quantitatively and preoperatively, which allows for more accurate and objective differential diagnoses, and more appropriate treatments and follow-up or additional examination strategies for the two subtypes. KEY POINTS: Preoperative determination of intrahepatic cholangiocarcinoma (ICC) subtype aids in surgical decision-making. Quantitative parameters from dynamic contrast-enhanced US (DCE-US) allow for the prediction of the ICC subtype. DCE-US-based imaging has the potential to become a novel complementary method for predicting ICC subtypes.

A non-invasive method to determine core temperature for cats and dogs using surface temperatures based on machine learning.

BACKGROUND: Rectal temperature (RT) is an important index of core temperature, which has guiding significance for the diagnosis and treatment of pet diseases. OBJECTIVES: Development and evaluation of an alternative method based on machine learning to determine the core temperatures of cats and dogs using surface temperatures. ANIMALS: 200 cats and 200 dogs treated between March 2022 and May 2022. METHODS: A group of cats and dogs were included in this study. The core temperatures and surface body temperatures were measured. Multiple machine learning methods were trained using a cross-validation approach and evaluated in one retrospective testing set and one prospective testing set. RESULTS: The machine learning models could achieve promising performance in predicting the core temperatures of cats and dogs using surface temperatures. The root mean square errors (RMSE) were 0.25 and 0.15 for cats and dogs in the retrospective testing set, and 0.15 and 0.14 in the prospective testing set. CONCLUSION: The machine learning model could accurately predict core temperatures for companion animals of cats and dogs using easily obtained body surface temperatures.