Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma.

BACKGROUND: To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression. METHODS: We retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis. RESULTS: For the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was - 0.03 and cumulative risk rates were calculated. DATA CONCLUSION: To assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.

Aggressive vertebral hemangiomas contain no adipose tissue resulting in thoracic spine kyphosis: A case report.

RATIONALE: Aggressive vertebral hemangiomas (AVHs) destroy continuous vertebral bodies and intervertebral discs and resulting in spinal kyphosis is extremely rare. The very aggressive behavior was attributable to its significant vascular component and contained no adipose tissue. PATIENT CONCERNS: We report a case of thoracic spine kyphosis of AVHs with multiple vertebral bodies and intervertebral disc destruction in a 45-year-old woman. DIAGNOSES: Based on the imaging studies, the patient underwent surgical removal of this lesion and spinal reconstruction. Histopathology consistent with vertebral hemangioma and contained no adipose. INTERVENTIONS: The patient underwent surgical removal of the lesion and spinal reconstruction. After subperiosteal dissection of the paraspinal muscles and exposure of the laminae, the laminae of the T5-7 vertebrae were removed and exposing the lesion. The lesion was soft and showed cystic changes, completely curetted and autogenous bone was implanted. Vertebroplasty was performed through T3-T9 pedicles bilaterally. Pedicle screw fixation was performed for segmental fixation and fusion. OUTCOMES: After 9 days of operation, the incision healed cleanly and free of pain. She was discharged in good general condition. The patient remained asymptomatic after follow-up 6 months of postoperative. LESSONS: AVHs destroy multiple vertebral bodies and intervertebral discs and resulting in spinal kyphosis is extremely rare.

Defensive glands in Stylotermitidae (Blattodea, Isoptera).

The large abundance of termites is partially achieved by their defensive abilities. Stylotermitidae represented by a single extant genus, Stylotermes, is a member of a termite group Neoisoptera that encompasses 83% of termite species and 94% of termite genera and is characterized by the presence of the frontal gland. Within Neoisoptera, Stylotermitidae represents a species-poor sister lineage of all other groups. We studied the structure of the frontal, labral and labial glands in soldiers and workers of Stylotermes faveolus, and the composition of the frontal gland secretion in S. faveolus and Stylotermes halumicus. We show that the frontal gland is a small active secretory organ in soldiers and workers. It produces a cocktail of monoterpenes in soldiers, and some of these monoterpenes and unidentified proteins in workers. The labral and labial glands are developed similarly to other termite species and contribute to defensive activities (labral in both castes, labial in soldiers) or to the production of digestive enzymes (labial in workers). Our results support the importance of the frontal gland in the evolution of Neoisoptera. Toxic, irritating and detectable monoterpenes play defensive and pheromonal functions and are likely critical novelties contributing to the ecological success of these termites.

Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study.

OBJECTIVE: To establish a model for predicting lymph node metastasis in bladder cancer (BCa) patients. METHODS: We retroactively enrolled 239 patients who underwent three-phase CT and resection for BCa in two centers (training set, n = 185; external test set, n = 54). We reviewed the clinical characteristics and CT features to identify significant predictors to construct a clinical model. We extracted the hand-crafted radiomics features and deep learning features of the lesions. We used the Minimum Redundancy Maximum Relevance algorithm and the least absolute shrinkage and selection operator logistic regression algorithm to screen features. We used nine classifiers to establish the radiomics machine learning signatures. To compensate for the uneven distribution of the data, we used the synthetic minority over-sampling technique to retrain each machine-learning classifier. We constructed the combined model using the top-performing radiomics signature and clinical model, and finally presented as a nomogram. We evaluated the combined model's performance using the area under the receiver operating characteristic, accuracy, calibration curves, and decision curve analysis. We used the Kaplan-Meier survival curve to analyze the prognosis of BCa patients. RESULTS: The combined model incorporating radiomics signature and clinical model achieved an area under the receiver operating characteristic of 0.834 (95% CI: 0.659-1.000) for the external test set. The calibration curves and decision curve analysis demonstrated exceptional calibration and promising clinical use. The combined model showed good risk stratification performance for progression-free survival. CONCLUSION: The proposed CT-based combined model is effective and reliable for predicting lymph node status of BCa patients preoperatively. CRITICAL RELEVANCE STATEMENT: Bladder cancer is a type of urogenital cancer that has a high morbidity and mortality rate. Lymph node metastasis is an independent risk factor for death in bladder cancer patients. This study aimed to investigate the performance of a deep learning radiomics model for preoperatively predicting lymph node metastasis in bladder cancer patients. KEY POINTS: • Conventional imaging is not sufficiently accurate to determine lymph node status. • Deep learning radiomics model accurately predicted bladder cancer lymph node metastasis. • The proposed method showed satisfactory patient risk stratification for progression-free survival.

Deep learning signature based on multiphase enhanced CT for bladder cancer recurrence prediction: a multi-center study.

Background: Accurate stratification of recurrence risk for bladder cancer (BCa) is essential for precise individualized therapy. This study aimed to develop and validate a model for predicting the risk of recurrence in BCa patients postoperatively using 3-phase enhanced CT images. Methods: We retrospectively enrolled 874 BCa patients across four centers between January 2006 and December 2021. Patients from one center were used as training set, while the remaining patients went into the validation set. We trained a deep learning (DL) model based on convolutional neural networks using 3-phase enhanced CT images. The resulting prediction scores were entered into Cox regression analysis to obtain DL scores and construct a DL signature. DL scores and clinical features were then used as deep learning radioclinical signature. The predictive performance of DL signature was assessed according to concordance index and area under curve compared with deep learning radioclinical signature, clinical model and a widely accepted staging grading system. Recurrence-free survival (RFS) and overall survival (OS) were also predicted in order to further assess survival benefits. Findings: DL signature showed strong power for predicting recurrence (concordance index, 0.869; area under curve, 0.889) in validation set, outperforming other models and system. In addition, we divided RFS and OS into high and low risk groups by selecting appropriate cutoff values for DL signature, and calculated cumulative recurrence risk rates for both groups. Interpretation: Our proposed DL signature shows promising potential as clinical aid for predicting postoperative recurrence risk in BCa and for stratifying the risk of RFS and OS, which can be applied to guide personalized precision therapy. Funding: There are no sources of funding for this manuscript.

Soldier phenotypic differences among 2 invasive and destructive Coptotermes species and their hybrids (Blattodea: Isoptera: Rhinotermitidae).

With recent evidence of hybridization events in the field, the phenotypic traits of F1 hybrid colonies of 2 destructive subterranean termite species, Coptotermes formosanus Shiraki and Coptotermes gestroi (Wasmann) remain to be investigated. In this study, laboratory colonies of 2 conspecific pairings and 2 heterospecific pairings (hybrid F = ♀C. formosanus × ♂C. gestroi, hybrid G = ♀C. gestroi × ♂C. formosanus) were examined in Florida, USA, and in Taiwan. Colony nest architecture for both hybrids displayed disorganized carton materials compared to the defined trabecular carton of both parental species. Soldier head measurements were not a reliable approach for diagnostic purposes, as soldier morphometric traits widely overlapped across all mating combinations, except for hybrid F soldiers displaying abnormally long mandibles. Hybrid F soldiers' mandibles also remained parallel when at rest. However, 4 qualitative morphological differences in soldiers were determined for diagnostic purposes. First, the fontanelle in both hybrids is horizontally ellipsoid whereas subcircular in C. gestroi and trianguliform in C. formosanus. Second, sclerotized striations along the postmental sulcus are present in C. gestroi, absent in C. formosanus, and intermediate in both hybrid soldier types. Third, each lateral margin of the fontanelle is flanked by 2 setae in C. formosanus and both hybrids, while a single seta resides on each side of the fontanelle in C. gestroi. Finally, C. gestroi and hybrid soldiers' heads are characterized by a bulging vertex that is lacking in C. formosanus. Therefore, a combination of these 4 characteristics now allows for soldier identification of hybrid Coptotermes.

Ambient PM2.5 Exposure and Bone Homeostasis: Analysis of UK Biobank Data and Experimental Studies in Mice and in Vitro.

BACKGROUND: Previous evidence has identified exposure to fine ambient particulate matter (PM2.5) as a leading risk factor for adverse health outcomes. However, to date, only a few studies have examined the potential association between long-term exposure to PM2.5 and bone homeostasis. OBJECTIVE: We sought to examine the relationship between long-term PM2.5 exposure and bone health and explore its potential mechanism. METHODS: This research included both observational and experimental studies. First, based on human data from UK Biobank, linear regression was used to explore the associations between long-term exposure to PM2.5 (i.e., annual average PM2.5 concentration for 2010) and bone mineral density [BMD; i.e., heel BMD (n=37,440) and femur neck and lumbar spine BMD (n=29,766)], which were measured during 2014-2020. For the experimental animal study, C57BL/6 male mice were assigned to ambient PM2.5 or filtered air for 6 months via a whole-body exposure system. Micro-computed tomography analyses were applied to measure BMD and bone microstructures. Biomarkers for bone turnover and inflammation were examined with histological staining, immunohistochemistry staining, and enzyme-linked immunosorbent assay. We also performed tartrate-resistant acid phosphatase (TRAP) staining and bone resorption assay to determine the effect of PM2.5 exposure on osteoclast activity in vitro. In addition, the potential downstream regulators were assessed by real-time polymerase chain reaction and western blot. RESULTS: We observed that long-term exposure to PM2.5 was significantly associated with lower BMD at different anatomical sites, according to the analysis of UK Biobank data. In experimental study, mice exposed long-term to PM2.5 exhibited excessive osteoclastogenesis, dysregulated osteogenesis, higher tumor necrosis factor-alpha (TNF-α) expression, and shorter femur length than control mice, but they demonstrated no significant differences in femur structure or BMD. In vitro, cells stimulated with conditional medium of PM2.5-stimulated macrophages had aberrant osteoclastogenesis and differences in the protein/mRNA expression of members of the TNF-α/Traf6/c-Fos pathway, which could be partially rescued by TNF-α inhibition. DISCUSSION: Our prospective observational evidence suggested that long-term exposure to PM2.5 is associated with lower BMD and further experimental results demonstrated exposure to PM2.5 could disrupt bone homeostasis, which may be mediated by inflammation-induced osteoclastogenesis. https://doi.org/10.1289/EHP11646.

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.

BACKGROUND: To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) preoperatively. METHODS: We retrospectively enrolled 688 patients with BCa (469 in the training cohort, 219 in the external test cohort) who underwent surgical resection. We extracted handcrafted radiomics (HCR) features and deep learning (DL) features from three-phase CT images (including corticomedullary-phase [C-phase], nephrographic-phase [N-phase] and excretory-phase [E-phase]). We constructed predictive models using 11 machine learning classifiers, and we developed a DLRN by combining the radiomic signature with clinical factors. We assessed performance and clinical utility of the models with reference to the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: The support vector machine (SVM) classifier model based on HCR and DL combined features was the best radiomic signature, with AUC values of 0.953 and 0.943 in the training cohort and the external test cohort, respectively. The AUC values of the clinical model in the training cohort and the external test cohort were 0.752 and 0.745, respectively. DLRN performed well on both data cohorts (training cohort: AUC = 0.961; external test cohort: AUC = 0.947), and outperformed the clinical model and the optimal radiomic signature. CONCLUSION: The proposed CT-based DLRN showed good diagnostic capability in distinguishing between high and low grade BCa.

The Trail-Following Communication in Stylotermes faveolus and S. halumicus (Blattodea, Isoptera, Stylotermitidae).

Stylotermitidae appear peculiar among all termites, feeding in trunks of living trees in South Asia only. The difficulty to collect them limits the ability to study them, and they thus still belong to critically unknown groups in respect to their biology. We used a combination of microscopic observations, chemical analysis and behavioural tests, to determine the source and chemical nature of the trail-following pheromone of Stylotermes faveolus from India and S. halumicus from Taiwan. The sternal gland located at the 5th abdominal segment was the exclusive source of the trail-following pheromone in both S. faveolus and S. halumicus, and it is made up of class I, II and III secretory cells. Using gas chromatography coupled mass spectrometry, (3Z)-dodec-3-en-1-ol (DOE) was identified as the trail-following pheromone which elicits strong behavioural responses in workers at a threshold around 10- 4 ng/cm and 0.1 ng/gland. Our results confirm the switch from complex aldehyde trail-following pheromones occurring in the basal groups to simpler linear alcohols in the ancestor of Kalotermitidae and Neoisoptera.

Preoperative contrast-enhanced CT-based radiomics nomogram for differentiating benign and malignant primary retroperitoneal tumors.

OBJECTIVES: This study evaluated the ability of a preoperative contrast-enhanced CT (CECT)-based radiomics nomogram to differentiate benign and malignant primary retroperitoneal tumors (PRT). METHODS: Images and data from 340 patients with pathologically confirmed PRT were randomly placed into training (n = 239) and validation sets (n = 101). Two radiologists independently analyzed all CT images and made measurements. Key characteristics were identified through least absolute shrinkage selection combined with four machine-learning classifiers (support vector machine, generalized linear model, random forest, and artificial neural network back propagation) to create a radiomics signature. Demographic data and CECT characteristics were analyzed to formulate a clinico-radiological model. Independent clinical variables were merged with the best-performing radiomics signature to develop a radiomics nomogram. The discrimination capacity and clinical value of three models were quantified by the area under the receiver operating characteristics (AUC), accuracy, and decision curve analysis. RESULTS: The radiomics nomogram was able to consistently differentiate between benign and malignant PRT in the training and validation datasets, with AUCs of 0.923 and 0.907, respectively. Decision curve analysis manifested that the nomogram achieved higher clinical net benefits than did separate use of the radiomics signature and clinico-radiological model. CONCLUSIONS: The preoperative nomogram is valuable for differentiating between benign and malignant PRT; it can also aid in treatment planning. KEY POINTS: • A noninvasive and accurate preoperative determination of benign and malignant PRT is crucial to identifying suitable treatments and predicting disease prognosis. • Associating the radiomics signature with clinical factors facilitates differentiation of malignant from benign PRT with improved diagnostic efficacy (AUC) and accuracy from 0.772 to 0.907 and from 0.723 to 0.842, respectively, compared with the clinico-radiological model alone. • For some PRT with anatomically special locations and when biopsy is extremely difficult and risky, a radiomics nomogram may provide a promising preoperative alternative for distinguishing benignity and malignancy.

Assessing the Mass Concentration of Microplastics and Nanoplastics in Wastewater Treatment Plants by Pyrolysis Gas Chromatography-Mass Spectrometry.

The level of microplastics (MPs) in wastewater treatment plants (WWTPs) has been well evaluated by the particle number, while the mass concentration of MPs and especially nanoplastics (NPs) remains unclear. In this study, pyrolysis gas chromatography-mass spectrometry was used to determine the mass concentrations of MPs and NPs with different size ranges (0.01-1, 1-50, and 50-1000 µm) across the whole treatment schemes in two WWTPs. The mass concentrations of total MPs and NPs decreased from 26.23 and 11.28 µg/L in the influent to 1.75 and 0.71 µg/L in the effluent, with removal rates of 93.3 and 93.7% in plants A and B, respectively. The proportions of NPs (0.01-1 µm) were 12.0-17.9 and 5.6-19.5% in plants A and B, respectively, and the removal efficiency of NPs was lower than that of MPs (>1 µm). Based on annual wastewater effluent discharge, it is estimated that about 0.321 and 0.052 tons of MPs and NPs were released into the river each year. Overall, this study investigated the mass concentration of MPs and NPs with a wide size range of 0.01-1000 µm in wastewater, which provided valuable information regarding the pollution level and distribution characteristics of MPs, especially NPs, in WWTPs.

HRCT1, negatively regulated by miR-124-3p, promotes tumor metastasis and the growth of gastric cancer by activating the ERBB2-MAPK pathway.

BACKGROUND: Gastric cancer is the fourth leading cause of cancer-related deaths worldwide. And patient outcomes are poor due to tumor relapse and metastasis. To develop new therapeutic strategies, it is of great importance to explore the mechanism underlying the progression of gastric cancer. METHODS: Primary gastric cancer samples with lymph node metastases (LNM) and without LNM were subjected to mRNA microarray assay. The differentially expressed genes were confirmed by RT-qPCR. HRCT1 protein expression was further detected using an immunohistochemistry (IHC) assay. In vitro and in vivo assays were performed to investigate the role of HRCT1 in tumor invasion, metastasis, and proliferation. The expressions of the downstream target genes of HRCT1 were detected by microarray, RT-qPCR and Western blot assays. Dual-luciferase reporter and Western blot assays were carried out to identify miRNAs target to HRCT1. RESULTS: HRCT1 was upregulated in gastric cancer, and high expression of HRCT1 was associated with poor overall survival (OS) and disease-free survival (DFS). Moreover, HRCT1protein expression was an independent predictor for poor OS and DFS. HRCT1 could promote gastric cancer cells' migration, invasion, and proliferation in vitro as well as tumor metastasis and growth in vivo. Notably, our data showed that HRCT1 promoted gastric cancer progression by activating the ERBB2-MAPK signaling pathway. At least partially, the expression of HRCT1 could be negatively regulated by miR-124-3p. CONCLUSIONS: The upregulated expression of HRCT1 predicts poor survival for patients with gastric cancer. HRCT1 promotes tumor progression by activating the ERBB2-MAPK pathway. HRCT1, negatively regulated by miR-124-3p, may be a potential therapeutic target for patients with gastric cancer.

Pathophysiological roles of integrins in gliomas from the perspective of glioma stem cells.

Glioblastoma is the most common primary intracranial tumor and is also one of the most malignant central nervous system tumors. Its characteristics, such as high malignancy, abundant tumor vasculature, drug resistance, and recurrence-prone nature, cause great suffering to glioma patients. Furthermore, glioma stem cells are the primordial cells of the glioma and play a central role in the development of glioma. Integrins-heterodimers composed of noncovalently bound a and ß subunits-are highly expressed in glioma stem cells and play an essential role in the self-renewal, differentiation, high drug resistance, and chemo-radiotherapy resistance of glioma stem cells through cell adhesion and signaling. However, there are various types of integrins, and their mechanisms of function on glioma stem cells are complex. Therefore, this article reviews the feasibility of treating gliomas by targeting integrins on glioma stem cells.

Nationwide Termite Pest Survey Conducted in Taiwan as a Citizen Science Project.

Information regarding the species composition and dispersal flight season of termites is crucial for termite management. The major obstacles to collecting such information are a lack of access to private buildings and shortage of workers to monitor and report on termite swarming. To overcome these difficulties, we launched a citizen science project in which members of the public and pest management professionals were invited to collect termite samples. We created the website, Taiwan Termite Identification Service, on which populace could log the collection information, and ship termite samples to our laboratory for identification. We also established a Facebook group, called the "Termite Forum," to publicize this project. A total of 3024 samples were collected from 2015 to 2020, and we identified the species of >93% of the samples. Based on 1499 samples collected from buildings, five structural termite pests were identified, and species composition in each county of Taiwan is available. According to 844 dispersal flight events, termite dispersal flight timing peak and degree of centralization were estimated using a Gaussian model. The collected data demonstrated that the invasive termite species, Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae), continued northward expansion. The first intercepted alate of Schedorhinotermes sp. (Blattodea: Rhinotermitidae) indicated that it may be a new invasive pest from Southeast Asia. This study reports on a successful case of a citizen science project where urban pest data were collected on a national scale.

Clinical Efficacy of Image-Guided Radiation Therapy for Cervical Cancer and Its Impact on Patients' Serum Tumor Markers and KPS Scores.

Objective: To assess the clinical efficacy of image-guided radiation therapy (IGRT) for cervical cancer and its impact on patients' serum tumor markers and Karnofsky Performance Status (KPS) scores. Methods: Between August 2018 and July 2020, 94 patients with cervical cancer diagnosed and treated in our hospital were recruited and assigned via the random number table method to receive either IGRT (study group) or conventional radiotherapy (control group), with 47 cases to each group. The primary endpoint was clinical efficacy, and secondary endpoints included serum tumor markers levels and KPS scores. Results: IGRT was associated with a significantly higher efficacy (97.87%) versus convention radiotherapy (74.46%) (P < 0.05). IGRT resulted in significantly lower levels of squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), carbohydrate antigen 50 (CA50), and carbohydrate antigen 724 (CA724) versus conventional radiotherapy (P < 0.05). The eligible patients after IGRT showed significantly higher KPS scores versus conventional radiotherapy (P < 0.05). Conclusion: IGRT enhances the survival of patients with cervical cancer, lowers their serum tumor marker levels, and elevates the KPS scores. Further clinical trials are, however, required prior to clinical promotion.

Oncogenic TRIB2 interacts with and regulates PKM2 to promote aerobic glycolysis and lung cancer cell procession.

PKM2 is an important regulator of the aerobic glycolysis that plays a vital role in cancer cell metabolic reprogramming. In general, Trib2 is considered as a "pseudokinase", contributing to different kinds of cancer. However, the detailed roles of TRIB2 in regulating cancer metabolism by PKM2 remain unclear. This study demonstrated that TRIB2, not a "pseudokinase", has the kinase activity to directly phosphorylate PKM2 at serine 37 in cancer cells. The elevated pSer37-PKM2 would subsequently promote the PKM2 dimers to enter into nucleus and increase the expression of LDHA, GLUT1, and PTBP1. The aerobic glycolysis is then elevated to promote cancer cell proliferation and migration in TRIB2- or PKM2-overexpressed cultures. The glucose uptake and lactate production increased, but the ATP content decreased in TRIB2- or PKM2-treated cultures. Experiments of TRIB2-/- mice further supported that TRIB2 could regulate aerobic glycolysis by PKM2. Thus, these results reveal the new kinase activity of TRIB2 and its mechanism in cancer metabolism may be related to regulating PKM2 to promote lung cancer cell proliferation in vitro and in vivo, suggesting promising therapeutic targets for cancer therapy by controlling cancer metabolism.

Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study.

Objectives: To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS). Methods: In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models. Result: Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models. Conclusion: The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

Functional Plasticity of Foraging Shelter Tubes Built by Termites.

Social insects' constructions are diverse and functionally flexible. We aimed to understand how termites modify their behavior and building material to change the function of a shelter tube. Construction behaviors of three termite species, Coptotermes formosanus Shiraki (Blattodea: Rhinotermitidae), Odontotermes formosanus (Shiraki) (Blattodea: Termitidae), and Nasutitermes takasagoensis (Nawa) (Blattodea: Termitidae), were recorded and analyzed. We measured the thickness and organic matter content of shelter tubes, and further tested their water loss and water drop resistance. All three termite species used a cement-brick construction procedure. The shelter tubes of C. formosanus and N. takasagoensis incorporating of woody material and feces present a strong resistance to water drops. Shelter tubes of the fungus-growing termite, O. formosanus, constructed using only soil and fluid secretion had a weak resistance to water drops. The trade-off between using feces to increase hydrophobicity of shelter tubes and using feces to grow fungus likely occurs in fungus-growing termites. Among intraspecific colonies, increasing the thickness of shelter tube improved resistance to water loss and water drops. This study demonstrated termites employed limited construction material and building behaviors to achieve functional plasticity of foraging shelter.

Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study.

OBJECTIVE: To assess the predictive ability of a multi-parametric MRI-based radiomics signature (RS) for the preoperative evaluation of Ki-67 proliferation status in sinonasal malignancies. METHODS: A total of 128 patients with sinonasal malignancies that underwent multi-parametric MRIs at two medical centres were retrospectively analysed. Data from one medical centre (n = 77) were used to develop the predictive models and data from the other medical centre (n = 51) constitute the test dataset. Clinical data and conventional MRI findings were reviewed to identify significant predictors. Radiomics features were determined using maximum relevance minimum redundancy and least absolute shrinkage and selection operator algorithms. Subsequently, RSs were established using a logistic regression (LR) algorithm. The predictive performance of RSs was assessed using calibration, decision curve analysis (DCA), accuracy, and AUC. RESULTS: No independent predictors of high Ki-67 proliferation were observed based on clinical data and conventional MRI findings. RS-T1, RS-T2, and RS-T1c (contrast enhancement T1WI) were established based on a single-parametric MRI. RS-Combined (combining T1WI, FS-T2WI, and T1c features) was developed based on multi-parametric MRI and achieved an AUC and accuracy of 0.852 (0.733-0.971) and 86.3%, respectively, on the test dataset. The calibration curve and DCA demonstrated an improved fitness and benefits in clinical practice. CONCLUSIONS: A multi-parametric MRI-based RS may be used as a non-invasive, dependable, and accurate tool for preoperative evaluation of the Ki-67 proliferation status to overcome the sampling bias in sinonasal malignancies. KEY POINTS: • Multi-parametric MRI-based radiomics signatures (RSs) are used to preoperatively evaluate the proliferation status of Ki-67 in sinonasal malignancies. • Radiomics features are determined using maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithms. • RSs are established using a logistic regression (LR) algorithm.

Clinical outcome of photodynamic therapy for the treatment of cervical intraepithelial neoplasia grade 2.

Five-aminolaevulinic acid photodynamic therapy (ALA-PDT) was used to treat 79 cervical intraepithelial neoplasia 2 (CIN 2) patients who desired preservation of fertility ,between Oct 2018 and Dec 2020. Three months after treatment, among the 65 patients who returned for follow-up, full recovery and improvement rates were 43/65 and 16/65, respectively, resulting in a total response rate of 90.77%. This suggests that ALA-PDT is worthy of clinical application, even as monotherapy. The result of immune testing also indicated significant promotion of CD4+T expression during the recovery process, highlighting the importance of immune responses in different prognoses.