Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-risk (OAR) sparing performance.With IRB approval, one hundred and twenty HN patients receiving IMRT were included. The DRL agent was trained with 20 patients.

Clinical commissioning and introduction of an in-house artificial intelligence (AI) platform for automated head and neck intensity modulated radiation therapy (IMRT) treatment planning.

Background And Purpose: To describe the clinical commissioning of an in-house artificial intelligence (AI) treatment planning platform for head-and-neck (HN) Intensity Modulated Radiation Therapy (IMRT).

Materials And Methods: The AI planning platform has three components: (1) a graphical user interface (GUI) is built within the framework of a commercial treatment planning system (TPS). The GUI allows AI models to run remotely on a designated workstation configured with GPU acceleration.

Understanding and modeling human-AI interaction of artificial intelligence tool in radiation oncology clinic using deep neural network: a feasibility study using three year prospective data.

Artificial intelligence (AI) based treatment planning tools are being implemented in clinic. However, human interactions with such AI tools are rarely analyzed. This study aims to comprehend human planner's interaction with the AI planning tool and incorporate the analysis to improve the existing AI tool.

Endothelial dysfunction in vascular complications of diabetes: a comprehensive review of mechanisms and implications.

Diabetic vascular complications are prevalent and severe among diabetic patients, profoundly affecting both their quality of life and long-term prospects. These complications can be classified into macrovascular and microvascular complications. Under the impact of risk factors such as elevated blood glucose, blood pressure, and cholesterol lipids, the vascular endothelium undergoes endothelial dysfunction, characterized by increased inflammation and oxidative stress, decreased NO biosynthesis, endothelial-mesenchymal transition, senescence, and even cell death.

Hot-Pressing Enhances Mechanical Strength of PEO Solid Polymer Electrolyte for All-Solid-State Sodium Metal Batteries.

Poly(ethylene oxide) (PEO)-based solid polymer electrolytes (SPEs) are widely utilized in all-solid-state sodium metal batteries (ASSSMBs) due to their excellent flexibility and safety. However, poor ionic conductivity and mechanical strength limit its development. In this work, an emerging solvent-free hot-pressing method is used to prepare mechanically robust PEO-based SPE, while sodium superionic conductors NaZrSiPO (NZSP) and NaClO are introduced to improve ionic conductivity.

Potassium sodium hydrogen citrate intervention on gut microbiota and clinical features in uric acid stone patients.

The high recurrence rate of renal uric acid stone (UAS) poses a significant challenge for urologists, and potassium sodium hydrogen citrate (PSHC) has been proven to be an effective oral dissolution drug. However, no studies have investigated the impact of PSHC on gut microbiota and its metabolites during stone dissolution therapy. We prospectively recruited 37 UAS patients and 40 healthy subjects, of which 12 patients completed a 3-month pharmacological intervention.

Achieving Dendrite-Free Solid-State Lithium-Metal Batteries via In Situ Construction of LiP/LiCl Interfacial Layers.

Hybrid solid electrolyte (HSE) exhibits potential as a solid electrolyte due to its satisfactory Li conductivity, superior flexibility, and optimal interface compatibility. However, the inadequate wettability of the Li/HSE interface leads to significant contact impedance, thus fostering the formation of Li dendrites and limiting their practical applicability. Here, a straightforward strategy to enhance the interfacial wettability between Li and HSE and promote the uniform migration of Li by in situ construction of a multifunctional interface consisting of LiP/LiCl (PCl@Li) was created.

Dynamic Chest Radiograph Simulation Technique with Deep Convolutional Neural Networks: A Proof-of-Concept Study.

In this study, we present an innovative approach that harnesses deep neural networks to simulate respiratory lung motion and extract local functional information from single-phase chest X-rays, thus providing valuable auxiliary data for early diagnosis of lung cancer. A novel radiograph motion simulation (RMS) network was developed by combining a U-Net and a long short-term memory (LSTM) network for image generation and sequential prediction. By utilizing a spatial transformer network to deform input images, our proposed network ensures accurate image generation.

Identification and validation of prognostic and tumor microenvironment characteristics of necroptosis index and BIRC3 in clear cell renal cell carcinoma.

Background: Necroptosis is a form of programmed cell death; it has an important role in tumorigenesis and metastasis. However, details of the regulation and function of necroptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. It is necessary to explore the significance of necroptosis in ccRCC.

A Crosstalk Between Castration-Resistant Prostate Cancer Cells, M2 Macrophages, and NK Cells: Role of the ATM-PI3K/AKT-PD-L1 Pathway.

Castration-resistant prostate cancer (CRPC) in males is associated with a poor prognosis and a higher risk of treatment-related adverse effects, with high mortality among cancers globally. It is thus imperative to explore novel potential molecules with dual therapeutic and biomarker functions. Based on the recent research findings, the expression levels of ataxia telangiectasia mutant kinase (ATM) in prostate cancer (PC) tissues collected from CRPC patients were higher than hormone-dependent PC patients.

Demethylase FTO inhibits the development of prostate cancer by upregulating EGR2 expression in an m6A manner.

Fat mass and obesity-associated protein (FTO) is a demethylase and plays a vital role in various cancers. However, the regulation mechanism of FTO in prostate cancer (PCa) remains unclear. This study aimed to elucidate the mechanism of FTO in PCa.

The altered composition of gut microbiota and biochemical features as well as dietary patterns in a southern Chinese population with recurrent renal calcium oxalate stones.

The correlation among gut microbiota, biochemical features, and dietary patterns in recurrent stone formers has been inadequately investigated in the Chinese population. Forty-two patients with calcium oxalate stones (CaOxS group), including 34 recurrent stone formers (RS group), and 40 nonstone healthy subjects (NS group) from Changshu Hospital Affiliated with Soochow University, were prospectively recruited. Food frequency questionnaires were completed by participants, fasting vein blood was extracted, 24-h urine was collected for biochemical detection, and fecal samples were gathered for 16S ribosomal RNA (rRNA) gene sequencing.

Identification of mitophagy-related biomarkers and immune infiltration in major depressive disorder.

Background: Major depressive disorder (MDD) is a life-threatening and debilitating mental health condition. Mitophagy, a form of selective autophagy that eliminates dysfunctional mitochondria, is associated with depression. However, studies on the relationship between mitophagy-related genes (MRGs) and MDD are scarce.

Deep learning attention-guided radiomics for COVID-19 chest radiograph classification.

Background: Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics to differentiate COVID-19, non-COVID-19 pneumonia and normal chest radiographs (CXR).

Methods: In this study, a deformable convolutional neural network (deformable CNN) was developed and used as a feature extractor to obtain 1,024-dimensional deep learning latent representation (DLR) features.

Modified the 8th AJCC staging system for patients with advanced prostate cancer: a study based on SEER database.

Background: The American Joint Committee on Cancer (AJCC) 8th staging system of prostate cancer may be insufficient in predicting the prognosis of some staged patients. This study aimed to modify the AJCC 8th staging system in patients with advanced prostate cancer.

Methods: Data of patients with advanced prostate cancer from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2016 were enrolled in this cohort study.

Identifying Prognostic Biomarkers Related to m6A Modification and Immune Infiltration in Renal Cell Carcinoma.

Background: Renal cell carcinoma (RCC) is the largest category of kidney tumors and usually does not have a good prognosis. N6-methyladenosine(m6A) and immune infiltration have received increased attention because of their great influence on the clinical outcome and prognosis of cancer patients.

Methods: We identified hub genes through multi-dimensional screening, including DEGs, PPI analysis, LASSO regression, and random forest.

Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier.

The COVID-19 pandemic has posed a significant global public health threat with an escalating number of new cases and death toll daily. The early detection of COVID-related CXR abnormality potentially allows the early isolation of suspected cases. Chest X-Ray (CXR) is a fast and highly accessible imaging modality.

Volumetric multiphase ventilation imaging based on four-dimensional computed tomography for functional lung avoidance radiotherapy.

Purpose: Current computed tomography (CT)-based lung ventilation imaging (CTVI) techniques derive a static ventilation image without temporal information. This research aims to develop a four-dimensional CT (4DCT)-based multiphase dynamic ventilation imaging framework capable of recovering the entire ventilation process throughout the breathing cycle for functional lung avoidance radiotherapy (FLART).

Methods: A total of 15 free-breathing thoracic 4DCT scans of lung or esophageal cancer patients were collected from the public datasets.

Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs.

Background: Coronavirus disease 2019 (COVID-19) is a pandemic disease. Fast and accurate diagnosis of COVID-19 from chest radiography may enable more efficient allocation of scarce medical resources and hence improved patient outcomes. Deep learning classification of chest radiographs may be a plausible step towards this.

Association of Gut Microbiota and Biochemical Features in a Chinese Population With Renal Uric Acid Stone.

Previous studies suggest that patients with nephrolithiasis exhibit dysbiosis in their gut microbiota, but those studies were conducted in calcium oxalate stone patients. We aimed to explore the association of gut microbiota and biochemical features of renal uric acid stone (UAS) patients in a Chinese population and identify the related bacteria that may affect the pathopoiesis of UAS. A case-control study of 117 patients with UAS, 123 patients with gout, and 135 healthy controls were included from January 2014 to October 2020.

Oncolytic Adenovirus with SPAG9 shRNA Driven by DD3 Promoter Improved the Efficacy of Docetaxil for Prostate Cancer.

Prostate cancer (PCa) is a common malignant tumor of the male urinary system and ranks the second in the causes of tumor-related deaths. Differential display code 3 (DD3) is a noncoding gene that is specifically expressed in PCa. High expression of sperm-associated antigen 9 (SPAG9) is closely related to tumorigenesis of PCa, and SPAG9 is a therapeutic target for PCa.

A case report of acute testicular pain secondary to segmental testicular infarction.

Background: Segmental testicular infarction is a rare condition that often occurs in the upper pole of the left testicle and usually presents with acute onset of scrotal pain. Contrast-enhanced ultrasound and MR are essential for diagnosing and differentiating segmental testicular infarction in clinical practice, and conservative treatment can only be adopted after a definitive diagnosis. In the present case, after conservative treatment, the infarct volume was reduced, the blood flow around the infarct was increased, and blood flow signals appeared in the infarct.

Deep Learning-Based Automatic Assessment of Radiation Dermatitis in Patients With Nasopharyngeal Carcinoma.

Purpose: Radiation dermatitis (RD) is a common, unpleasant side effect of patients receiving radiation therapy. In clinical practice, the severity of RD is graded manually through visual inspection, which is labor intensive and often leads to large interrater variations. To overcome these shortcomings, this study aimed to develop an automatic RD assessment based on deep learning (DL) techniques that could efficiently assist the RD severity classification in clinical application.

Bioinformatics analysis of the clinical relevance of CDCA gene family in prostate cancer.

Background: Prostate cancer (PCa) is the second most frequent cancer in men worldwide, and its mortality rate is increasing every year. The cell division cycle-associated (CDCA) gene family plays vital roles in the cell cycle process, but an analysis of these proteins in PCa is still lacking.

Methods: UALCAN and GEPIA were used to examine the transcriptional data and survival of the CDCA gene family in PCa patients.