Exploring deep learning strategies for intervertebral disc herniation detection on veterinary MRI.

Intervertebral Disc Herniation (IVDH) is a common spinal disease in dogs, significantly impacting their health, mobility, and overall well-being. This study initiates an effort to automate the detection and localization of IVDH lesions in veterinary MRI scans, utilizing advanced artificial intelligence (AI) methods. A comprehensive canine IVDH dataset, comprising T2-weighted sagittal MRI images from 213 pet dogs of various breeds, ages, and sizes, was compiled and utilized to train and test the IVDH detection models. The experimental results showed that traditional two-stage detection models reliably outperformed one-stage models, including the recent You Only Look Once X (YOLOX) detector. In terms of methodology, this study introduced a novel spinal localization module, successfully integrated into different object detection models to enhance IVDH detection, achieving an average precision (AP) of up to 75.32%. Additionally, transfer learning was explored to adapt the IVDH detection model for a smaller feline dataset. Overall, this study provides insights into advancing AI for veterinary care, identifying challenges and exploring potential strategies for future development in veterinary radiology.

Consensus for antifungal stewardship in China (2024 edition).

Background: Invasive fungal disease (IFD) has become a serious threat to human health in China and around the world, with high mortality and morbidity. Currently, the misdiagnosis rate of IFD is extremely high, compounded with the low quality of prescription antifungals and the high incidence of adverse events associated with IFD treatment, resulting in lengthy hospitalization, low clinical response, and high disease burden, which have become serious challenges in clinical practice. Antifungal stewardship (AFS) can not only significantly increase the early diagnosis rate of IFD, reduce inappropriate utilization of antifungal drugs, improve patient prognosis, but can also improve therapeutic safety and reduce healthcare expenses. Thus, it is urgent to identify key AFS metrics suitable for China's current situation. Methods: Based on metrics recommended by international AFS consensuses, combined with the current situation of China and the clinical experience of authoritative experts in various fields, several metrics were selected, and experts in the fields of respiratory diseases, hematology, intensive care units (ICUs), dermatology, infectious diseases, microbiology laboratory and pharmacy were invited to assess AFS metrics by the Delphi method. Consensus was considered to be reached with an agreement level of ≥80% for the metric. Results: Consensus was reached for 24 metrics, including right patient metrics (n=4), right time metrics (n=3), and right use metrics (n=17). Right use metrics were further subdivided into drug choice (n=8), drug dosage (n=4), drug de-escalation (n=1), drug duration (n=2), and drug consumption (n=2) metrics. Forty-six authoritative experts assessed and reviewed the above metrics, and a consensus was reached with a final agreement level of ≥80% for 22 metrics. Conclusions: This consensus is the first to propose a set of AFS metrics suitable for China, which helps to establish AFS standards in China and is also the first AFS consensus in Asia, and may improve the standard of clinical diagnosis and treatment of IFD, and guide hospitals to implement AFS, ultimately promoting the rational use of antifungal drugs and improving patient prognosis.

Ischemic perfusion radiomics: assessing neurological impairment in acute ischemic stroke.

Introduction: Accurate neurological impairment assessment is crucial for the clinical treatment and prognosis of patients with acute ischemic stroke (AIS). However, the original perfusion parameters lack the deep information for characterizing neurological impairment, leading to difficulty in accurate assessment. Given the advantages of radiomics technology in feature representation, this technology should provide more information for characterizing neurological impairment. Therefore, with its rigorous methodology, this study offers practical implications for clinical diagnosis by exploring the role of ischemic perfusion radiomics features in assessing the degree of neurological impairment. Methods: This study employs a meticulous methodology, starting with generating perfusion parameter maps through Dynamic Susceptibility Contrast-Perfusion Weighted Imaging (DSC-PWI) and determining ischemic regions based on these maps and a set threshold. Radiomics features are then extracted from the ischemic regions, and the t-test and least absolute shrinkage and selection operator (Lasso) algorithms are used to select the relevant features. Finally, the selected radiomics features and machine learning techniques are used to assess the degree of neurological impairment in AIS patients. Results: The results show that the proposed method outperforms the original perfusion parameters, radiomics features of the infarct and hypoxic regions, and their combinations, achieving an accuracy of 0.926, sensitivity of 0.923, specificity of 0.929, PPV of 0.923, NPV of 0.929, and AUC of 0.923, respectively. Conclusion: The proposed method effectively assesses the degree of neurological impairment in AIS patients, providing an objective auxiliary assessment tool for clinical diagnosis.

TBN as Organic Redox Cocatalyst for Oxidative Tiffeneau-Demjanov-Type Rearrangement Using O2 as Sole Oxidant.

The Tiffeneau-Demjanov-type rearrangement is a ring-expansion reaction involving the cationic rearrangement of cyclic alcohols. The carbocation intermediates can be generated in situ via various means, including Wacker oxidation. In near recent reports on the reinvestiagtions by Wahl et al. (Sietmann, J.; Tenberge, M.; Wahl, J. M. Wacker Oxidation of Methylenecyclobutanes: Scope and Selectivity in an Unusual Setting. Angew. Chem., Int. Ed. 2023, 62, e202215381) and Zhu et al. (Feng, Q.; Wang, Q.; Zhu, J.-P. Oxidative Rearrangement of 1,1-Disubstituted Alkenes to Ketones. Science 2023, 379, 1363-1368), stoichiometric oxidants were involved. In this work, we report the Tiffeneau-Demjanov-type rearrangement can be smoothly promoted by the Pd-TBN cocatalyzed aerobic Wacker oxidation using molecular oxygen as the sole oxidant. tert-Butanol is essential for achieving high yields. Since the first report by Grigg et al. in 1977 (Boontanonda, P.; Grigg, R. J. Palladium (II)-Catalysed Ring Expansion of Methylenecyclobutanes and Related Systems. J. Chem. Soc. Chem. Commun. 1977, 17, 583-584), the five-decade journey of Pd-catalyzed Tiffeneau-Demjanov-type rearrangement returns to the aerobic again.

Critical role of benthic fauna in enhancing nanoplastics removal in constructed wetland: Performance, fate and mechanism.

The presence of nanoplastics (NPs) in wastewater poses a considerable risk to ecosystems. Although constructed wetlands (CWs) have the potential to removal NPs, their efficiency is limited by insufficient consideration of ecosystem integrity. Herein, three typical benthic fauna (Corbicula fluminea, Chironomus riparius and Tubifex tubifex) were added to CWs to improve the ecological integrity of CWs, and further enhance the ecological benefits. Results indicated that the addition of C. fluminea, C. riparius and T. tubifex increased NPs removal by 19.14 %, 17.02 %, and 15.76 % than that without benthic faunas, respectively. Based on fluorescence signal analysis, the presence of benthic fauna could intake NPs, and enhanced the adsorption of NPs by plants. The addition of C. fluminea significantly increased catalase (1541.82 ± 41.35 U/g), glutathione S-transferase (0.34 ± 0.02 U/g), and superoxide dismutase (116.33 ± 6.91 U/g) activities (p < 0.05) as a defense mechanism against NPs-induced oxidative stress. Metagenomic analysis revealed that the abundances of key enzymes involved in glycolysis, the tricarboxylic acid cycle, and polystyrene metabolism pathways were increased when C. fluminea was added, corresponding to the microbial degradation of NPs. Overall, the results of this study implied that the benthic fauna can efficiently remove NPs from wastewater in CWs.

Implications of YWHAH Gene Expression in the Early Detection of Sepsis.

ABSTRACT: Sepsis, a complex and multifaceted condition, is a common occurrence with serious implications for critically ill patients in the Intensive Care Unit (ICU). The YWHAH gene encodes the 14-3-3n protein, a member of the 14-3-3 protein family. While existing research primarily focuses on the role of 14-3-3n in conditions such as schizophrenia and various cancers, our study revealed that the expression of the YWHAH gene remained relatively stable in both infected individuals and healthy controls. Through Venn plot analysis following weighted gene correlation network analysis (WGCNA), we observed a potential association between elevated YWHAH expression and the transition from infection to sepsis. In a comprehensive analysis of public single-cell transcriptome databases, the expression of YWHAH was found to be distinctive in cases of sepsis and infection. These findings were corroborated through an in vitro analysis utilizing real-time polymerase chain reaction. This study represents the initial identification of variations in YWHAH gene expression between patients with infection and sepsis, potentially offering insights for the development of early detection and treatment strategies for sepsis.

Synthesis Enabled by E-to-Z Isomerization Using CBZ6 as Energy Transfer Photocatalyst.

The reactions of Z-isomers and E-isomers usually are different in consideration of the regioselectivity of chemoselectivity. The syntheses of Z-isomers are not feasible in many cases. The energy transfer (EnT) E/Z-photoisomerization might yield the Z-isomers. In this work, CBZ6 was proven to be an EnT photocatalyst for the E → Z-isomerization of C-C or C-N double bonds. The transformations of in situ generated Z-isomers of oximes and stilbenes consequently afforded the desired reversed Beckmann rearrangement products and phenanthrenes, respectively.

Nirmatrelvir and ritonavir for inpatients with severe or critical COVID-19 beyond five days of symptom onset: a propensity score-matched, multicenter, retrospective cohort study.

BACKGROUND: There is an urgent need for therapeutic strategies for inpatients with severe or critical COVID-19. The evaluation of the clinical benefits of nirmatrelvir and ritonavir (Nmr/r) for these patients beyond five days of symptom onset is insufficient. METHODS: A new propensity score-matched cohort was constructed by using multicenter data from 6695 adult inpatients with COVID-19 from December 2022 to February 2023 in China after the epidemic control measures were lifted across the country. The severity of disease of the inpatients was based on the tenth trial edition of the Guidelines on the Diagnosis and Treatment of COVID-19 in China. The symptom onset of 1870 enrolled severe or critical inpatients was beyond five days, and they received either Nmr/r plus standard treatment or only standard care. The ratio of patients whose SOFA score improved more than 2 points, crucial respiratory endpoints, changes in inflammatory markers, safety on the seventh day following the initiation of Nmr/r treatment, and length of hospital stay were evaluated. RESULTS: In the Nmr/r group, on Day 7, the number of patients with an improvement in SOFA score ≥ 2 was much greater than that in the standard treatment group (P = 0.024) without a significant decrease in glomerular filtration rate (P = 0.815). Additionally, the rate of new intubation was lower (P = 0.004) and the no intubation days were higher (P = 0.003) in the first 7 days in the Nmr/r group. Other clinical benefits were limited. CONCLUSIONS: Our study may provide new insight that inpatients with severe or critical COVID-19 beyond five days of symptom onset benefit from Nmr/r. Future studies, particularly randomized controlled trials, are necessary to verify the above findings.

Enhancing antimicrobial resistance detection with MetaGeneMiner: Targeted gene extraction from metagenomes.

BACKGROUND: Accurately and efficiently extracting microbial genomic sequences from complex metagenomic data is crucial for advancing our understanding in fields such as clinical diagnostics, environmental microbiology, and biodiversity. As sequencing technologies evolve, this task becomes increasingly challenging due to the intricate nature of microbial communities and the vast amount of data generated. Especially in intensive care units (ICUs), infections caused by antibiotic-resistant bacteria are increasingly prevalent among critically ill patients, significantly impacting the effectiveness of treatments and patient prognoses. Therefore, obtaining timely and accurate information about infectious pathogens is of paramount importance for the treatment of patients with severe infections, which enables precisely targeted anti-infection therapies, and a tool that can extract microbial genomic sequences from metagenomic dataset would be of help. METHODS: We developed MetaGeneMiner to help with retrieving specific microbial genomic sequences from metagenomes using a k-mer-based approach. It facilitates the rapid and accurate identification and analysis of pathogens. The tool is designed to be user-friendly and efficient on standard personal computers, allowing its use across a wide variety of settings. We validated MetaGeneMiner using eight metagenomic samples from ICU patients, which demonstrated its efficiency and accuracy. RESULTS: The software extensively retrieved coding sequences of pathogens Acinetobacter baumannii and herpes simplex virus type 1 and detected a variety of resistance genes. All documentation and source codes for MetaGeneMiner are freely available at https://gitee.com/sculab/MetaGeneMiner. CONCLUSIONS: It is foreseeable that MetaGeneMiner possesses the potential for applications across multiple domains, including clinical diagnostics, environmental microbiology, gut microbiome research, as well as biodiversity and conservation biology. Particularly in ICU settings, MetaGeneMiner introduces a novel, rapid, and precise method for diagnosing and treating infections in critically ill patients. This tool is capable of efficiently identifying infectious pathogens, guiding personalized and precise treatment strategies, and monitoring the development of antibiotic resistance, significantly impacting the diagnosis and treatment of severe infections.

Recent advances in flexible hydrogel sensors: Enhancing data processing and machine learning for intelligent perception.

With the advent of flexible electronics and sensing technology, hydrogel-based flexible sensors have exhibited considerable potential across a diverse range of applications, including wearable electronics and soft robotics. Recently, advanced machine learning (ML) algorithms have been integrated into flexible hydrogel sensing technology to enhance their data processing capabilities and to achieve intelligent perception. However, there are no reviews specifically focusing on the data processing steps and analysis based on the raw sensing data obtained by flexible hydrogel sensors. Here we provide a comprehensive review of the latest advancements and breakthroughs in intelligent perception achieved through the fusion of ML algorithms with flexible hydrogel sensors, across various applications. Moreover, this review thoroughly examines the data processing techniques employed in flexible hydrogel sensors, offering valuable perspectives expected to drive future data-driven applications in this field.

Development of the near-infrared fluorescence probe for detection of ONOO- and its application in vitro and vivo.

Diabetes has become one of the most common endocrine and metabolic diseases threatening human health, which can induce mitochondrial dysfunction and exacerbate the excessive production of reactive oxygen species (ROS). Among them, ONOO- level fluctuation was closely related to diabetes. Hence, it is of great significance to develop a near-infrared fluorescence probe for visualizing ONOO- level fluctuations in diabetes. In this paper, we constructed a fluorescence probe YBL with dicyano-isophorone derivative as fluorophore and diphenyl phosphate as ONOO- response site, which can detect ONOO- with the low detection limit (39.8 nM) and exhibit excellent selectivity and sensitivity. The probe YBL has been applied to monitor intracellular ONOO- level fluctuations. Meanwhile, the image results showed that high sugar promoted the increase of ONOO- level in cells. More important, the probe YBL can be used for imaging in mice, and the results showed that content of ONOO- was increased in diabetic mice. Therefore, the probe YBL provided a tool for understanding diabetes progression by imaging ONOO-.

Loop technique for anterior cruciate ligament reconstruction combined with anterolateral structure reinforcement: technical description and clinical results.

PURPOSE: We describe a surgical technique for ACL reconstruction combined with anterolateral structure reinforcement and report early clinical follow-up results. METHODS: The semitendinosus and gracilis tendons are braided into 5 strands and the ACL femoral tunnel and tibial tunnel are created. The graft is passed through the tunnel with the use of a traction suture and the tibial end is fixed with absorbable interference screws at 30° of knee flexion. The ACL graft traction suture is used as an anterolateral reconstruction structure to pass through the proximal exit of the ACL femoral tunnel and then through the depth of the iliotibial bundle to the anterior to Gerdy's tubercle, a bony tunnel is created from the anterior to Gerdy's tubercle to the goose foot, and the traction suture is passed through this bony tunnel to form a Loop structure at 20° of knee flexion. Between March 2021 and May 2022 IKDC score, Lysholm score, and Tegner score were performed preoperatively and 6-12 months postoperatively in 24 consecutive patients who met the indications for this procedure and underwent surgery. The patient's maximum flexion angle, the circumference of the thigh, and the stress X-ray between the operated and healthy knee were measured. RESULTS: Patients showed significant improvement in IKDC score, Lysholm score and Tegner score at a mean follow-up of 7 months postoperatively compared to preoperatively. No significant increase in anterior tibial displacement was found between the patient's operated side and the healthy side. CONCLUSION: The Loop technique ACLR combined with ALSA can be used in patients with an ACL tear combined with a high degree of positive pivot shift. The patient's subjective perception was significantly improved from the preoperative period and knee stability was restored. LEVEL OF EVIDENCE: IV, therapeutic study.

A fluorescence probe with targeted mitochondria for detecting hydrogen peroxide in vitro and in diabetic mice.

We designed and prepared probe W-1 for the detection of H2O2. W-1 showed excellent selectivity for H2O2 and was accompanied by colorimetric signal changes. The excellent linear relationship between fluorescence intensity and H2O2 concentration (0-100 µM) provided favorable conditions for its quantitative detection. In addition, the combination of portable test strips with a smartphone platform provided great convenience for on-site visual detection of H2O2. Moreover, W-1 possessed targeting mitochondria property and could be applied to image the exogenous and endogenous H2O2 in cells to distinguish normal cells and cancer cells. Lastly, W-1 was used for monitoring the H2O2 fluctuation of the diabetic process in mice, and the results showed an increase in H2O2 levels in diabetes. Therefore, the probe provided a tool for understanding the pathological and physiological mechanisms of diabetes by imaging H2O2.

Topic Modeling Analysis of Chinese Medicine Literature on Gastroesophageal Reflux Disease: Insights into Potential Treatment.

OBJECTIVE: To analyze Chinese medicine (CM) prescriptions for gastroesophageal reflux disease (GERD), we model topics on GERD-related classical CM literature, providing insights into the potential treatment. METHODS: Clinical guidelines were used to identify symptom terms for GERD, and CM literature from the database "Imedbooks" was retrieved for related prescriptions and their corresponding sources, indications, and other information. BERTopic was applied to identify the main topics and visualize the data. RESULTS: A total of 36,207 entries are queried and 1,938 valid entries were acquired after manually filtering. Eight topics were identified by BERTopic, including digestion function abate, stomach flu, respiratory-related symptoms, gastric dysfunction, regurgitation and gastrointestinal dysfunction in pediatric patients, vomiting, stroke and alcohol accumulation are associated with the risk of GERD, vomiting and its causes, regurgitation, epigastric pain, and symptoms of heartburn. CONCLUSIONS: Topic modeling provides an unbiased analysis of classical CM literature on GERD in a time-efficient and scale-efficient manner. Based on this analysis, we present a range of treatment options for relieving symptoms, including herbal remedies and non-pharmacological interventions such as acupuncture and dietary therapy.

Blood Urine Nitrogen Trajectories of Acute Pancreatitis Patients in Intensive Care Units.

Objective: To identify subclasses of acute pancreatitis (AP) patients in the intensive care unit (ICU) by analyzing blood urea nitrogen (BUN) trajectories. Methods: AP patients in West China Hospital System (development cohort) and three public databases in the United States (validation cohort) were included. Latent class trajectory modelling was used to identify subclasses based on BUN trajectories within the first 21 days after ICU admission. Clinical characteristics and outcomes were compared, and results were externally validated. Results: The study comprised 2971 and 930 patients in the development and validation cohorts, respectively, with five subclasses: Class 1 ("Moderate-azotemia, slow decreasing"), Class 2 ("Non-azotemia"), Class 3 ("Severe-azotemia, slow decreasing"), Class 4 ("Moderate-azotemia, rapid increasing"), and Class 5 ('Moderate-azotemia, slow increasing) identified. Azotemia patients showed significantly higher 30-day mortality risk in development and validation cohorts. Specifically, Class 4 patients exhibited notably highest mortality risk in both the development cohort (HR 5.32, 95% CI 2.62-10.82) and validation cohort (HR 6.23, 95% CI 2.93-13.22). Regarding clinical characteristics, AP patients in Class 4 showed lower mean arterial pressure and a higher proportion of renal disease. We also created an online early classification model to further identify Class 4 patients among all patients with moderate azotemia at baseline. Conclusion: This multinational study uncovers heterogeneity in BUN trajectories among AP patients. Patients with "Moderate-azotemia, rapid increasing" trajectory, had a higher mortality risk than patients with severe azotemia at baseline. This finding complements studies that solely rely on baseline BUN for risk stratification and enhanced our understanding of longitudinal progression of AP.

Extra-abdominal growth of a large low-grade appendiceal mucinous tumour through the femoral canal-a rare case report.

Low-grade appendiceal mucinous neoplasms (LAMNs) are rare and heterogeneous diseases that, despite their increased incidence, are well differentiated, tend to be painless, and histologically lack distinctive invasive features without infiltrative growth, destructive infiltration, or associated pro-fibroproliferative responses. However, the biological behaviour of these tumours is difficult to determine preoperatively or intraoperatively, and the possibility of rupture puts patients at risk for peritoneal pseudomucinous neoplasms (PMPs).Patients with low-grade appendiceal mucinous tumours and peritoneal pseudomucinous tumours experience slow disease progression and are incurable and have a high risk of recurrence, morbidity, and ultimately death, despite the reported 5- and 10-year survival rates of 50-86% and 45-68%, respectively. In this article, we report the case of a 80-year-old male with a giant low-grade appendiceal mucinous tumour associated with a peritoneal pseudomucinous tumour, and discuss the diagnostic and management strategies for giant low-grade appendiceal mucinous tumours in the context of a literature review.

LINC00152: Potential driver oncogene in pan-cancer.

Long noncoding RNAs (lncRNA) are a class of non-coding RNAs greater than 200 bp in length with limited peptide-coding function. The transcription of LINC00152 is derived from chromosome 2p11.2. Many studies prove that LINC00152 influences the progression of various tumors via promoting the tumor cells malignant phenotype, chemoresistance, and immune escape. LINC00152 is regulated by multiple transcription factors and DNA hypomethylation. In addition, LINC00152 participates in the regulation of complex molecular signaling networks through epigenetic regulation, protein interactions, and competitive endogenous RNA (ceRNA). Here, we provide a systematic review of the upstream regulatory factors of LINC00152 expression level in different types of tumors. In addition, we revisit the main functions and mechanisms of LINC00152 as driver oncogene and biomarker in pan-cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Methods > RNA Analyses in Cells RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

A 3D pseudo-continuous arterial spin labeling study of altered cerebral blood flow correlation networks in mild cognitive impairment and Alzheimer's disease.

Objective: To investigate the abnormalities of the three-dimensional pseudo-continuous arterial spin labeling (3D PCASL) based cerebral blood flow (CBF) correlation networks in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Methods: 3D PCASL images of 53 cognitive normal (CN) subjects, 43 subjects with MCI, and 30 subjects with AD were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Whole-brain CBF maps were calculated using PCASL and proton density-weighted images (PDWI). The 246 regional CBF values, including the cortex and subcortex, were obtained after registering the Brainnetome Atlas to the individual CBF maps. The Pearson correlation coefficient between every two regions across subjects was calculated to construct the CBF correlation network. Then the topologies of CBF networks with regard to global properties (global network efficiency, clustering coefficient, characteristic path length, and small-world properties), hub regions, nodal properties (betweenness centrality, BC), and connections were compared among CN, MCI, and AD. Significant changes in the global and nodal properties were observed in the permutation tests, and connections with significant differences survived after the z-statistic and false discovery rate (FDR) correction. Results: The CBF correlation networks of CN, MCI, and AD all showed small-world properties. Compared with CN, global efficiency decreased significantly in AD. Significant differences in nodal properties and a loss of hub regions are noted in the middle temporal lobe in both MCI and AD. In the frontal lobe, BC is reduced in MCI while it is increased in the occipital lobe in AD. The identified altered hub regions with significant differences in MCI and AD were mainly distributed in the hippocampus and entorhinal cortex. In addition, disrupted hub regions in AD with significantly decreased connections were mainly found in the precuneus/posterior cingulate cortex (PCC) and hippocampus-cortical cortex. Conclusions: Noninvasive 3D PCASL-based CBF correlation networks are capable of showing changes in topological organization in subjects with MCI and AD, and the observed disruption in the topological organization may underlie cognitive decline in MCI and AD.

When can we start early enteral nutrition safely in patients with shock on vasopressors?

Shock is a common critical illness characterized by microcirculatory disorders and insufficient tissue perfusion. Patients with shock and hemodynamic instability generally require vasopressors to maintain the target mean arterial pressure. Enteral nutrition (EN) is an important therapeutic intervention in critically ill patients and has unique benefits for intestinal recovery. However, the initiation of early EN in patients with shock receiving vasopressors remains controversial. Current guidelines make conservative and vague recommendations regarding early EN support in patients with shock. Increasing studies demonstrates that early EN delivery is safe and feasible in patients with shock receiving vasopressors; however, this evidence is based on observational studies. Changes in gastrointestinal blood flow vary by vasopressor and inotrope and are complex. The risk of gastrointestinal complications, especially the life-threatening complications of non-occlusive mesenteric ischemia and non-occlusive bowel necrosis, cannot be ignored in patients with shock during early EN support. It remains a therapeutic challenge in critical care nutrition therapy to determine the initiation time of EN in patients with shock receiving vasopressors and the safe threshold region for initiating EN with vasopressors. Therefore, the current review aimed to summarize the evidence on the optimal and safe timing of early EN initiation in patients with shock receiving vasopressors to improve clinical practice.

Customized m-RCNN and hybrid deep classifier for liver cancer segmentation and classification.

Diagnosing liver disease presents a significant medical challenge in impoverished countries, with over 30 billion individuals succumbing to it each year. Existing models for detecting liver abnormalities suffer from lower accuracy and higher constraint metrics. As a result, there is a pressing need for improved, efficient, and effective liver disease detection methods. To address the limitations of current models, this method introduces a deep liver segmentation and classification system based on a Customized Mask-Region Convolutional Neural Network (cm-RCNN). The process begins with preprocessing the input liver image, which includes Adaptive Histogram Equalization (AHE). AHE helps dehaze the input image, remove color distortion, and apply linear transformations to obtain the preprocessed image. Next, a precise region of interest is segmented from the preprocessed image using a novel deep strategy called cm-RCNN. To enhance segmentation accuracy, the architecture incorporates the ReLU activation function and the modified sigmoid activation function. Subsequently, a variety of features are extracted from the segmented image, including ResNet features, shape features (area, perimeter, approximation, and convex hull), and enhanced median binary pattern. These extracted features are then used to train a hybrid classification model, which incorporates classifiers like SqueezeNet and DeepMaxout models. The final classification outcome is determined by averaging the scores obtained from both classifiers.