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Objective To study the effect of artificial intelligence in the pathological diagnosis of periapical cysts and to explore the application of artificial intelligence in the field of oral pathology. Methods Pathological images of eighty-seven periapical cysts were selected as subjects to read, and a neural network with a U-net structure was constructed. The 87 HE images and labeled images of periapical cysts were divided into a training set (72 images) and a test set (15 images), which were used in the training model and test model, respectively. Finally, the target level index F1 score, pixel level index Dice coefficient and receiver operating characteristic (ROC) curve were used to evaluate the ability of the U-net model to recognize periapical cyst epithelium. Results The F1 score of the U-net network model for recognizing periapical cyst epithelium was 0.75, and the Dice index and the areas under the ROC curve were 0.685 and 0.878, respectively. Conclusion The U-net network model constructed by artificial intelligence has a good segmentation result in identifying periapical cyst epithelium, which can be preliminarily applied in the pathological diagnosis of periapical cysts and is expected to be gradually popularized in clinical practice after further verification with large samples.

Results of previous studies have suggested that cardiovascular autonomic neuropathy (CAN) may predict rapid kidney function decline among people with diabetes. We analyzed the association between baseline CAN and subsequent glomerular filtration rate (GFR) decline among individuals with type 1 diabetes (T1D) from the Preventing Early Renal Loss in Diabetes (PERL) study (N = 469) and with type 2 diabetes (T2D) from Action to Control Cardiovascular Risk in Diabetes (ACCORD) (N = 7,973). Baseline CAN was ascertained with electrocardiogram-derived heart rate variability indices. Its association with GFR slopes, rapid kidney function decline (GFR loss of ≥5 mL/min/1.73 m2/year), and ≥40% GFR loss was evaluated by linear mixed-effects, logistic, and Cox regression, respectively. Participants with CAN experienced more rapid GFR decline, by an excess 1.15 mL/min/1.73 m2/year (95% CI −1.93 to −0.37; P = 4.0 × 10−3) in PERL and 0.34 mL/min/1.73 m2/year (95% CI −0.49 to −0.19; P = 6.3 × 10−6) in ACCORD. This translated to 2.11 (95% CI 1.23–3.63; P = 6.9 × 10−3) and 1.39 (95% CI 1.20–1.61; P = 1.1 × 10−5) odds ratios of rapid kidney function decline in PERL and ACCORD, respectively. Baseline CAN was also associated with a greater risk of ≥40% GFR loss events during follow-up (hazard ratio 2.60 [95% CI 1.15–5.45], P = 0.02, in PERL and hazard ratio 1.54 [95% CI 1.28–1.84], P = 3.8 × 10−6, in ACCORD). These associations remained significant after adjustment for potential confounders, including baseline GFR and albuminuria. Our findings indicate that CAN is a strong, independent predictor of rapid kidney function decline in both T1D and T2D. Further studies of the link between these two complications may help with development of new therapies to prevent kidney function decline in patients with diabetes. Article Highlights: Cardiovascular autonomic neuropathy is a strong and independent predictor of rapid kidney function decline in both type 1 and type 2 diabetes. Autonomic nervous system dysfunction may serve as a novel target to develop new therapies to prevent kidney function loss in diabetes. Electrocardiogram-derived indices of cardiovascular autonomic neuropathy might be useful, when added to known clinical risk factors, to improve the identification of patients at high risk of rapid kidney function loss and select them for intensive preventive treatments. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) Pd–In2O3/rGO aerogel was fabricated via a one-step hydrothermal treatment and freeze-drying. The morphology and structure of the 3D Pd–In2O3/rGO aerogel were examined. The aerogel material had a porous network structure, which was particularly advantageous for gas adsorption. The Pd–In2O3 nanoparticles were uniformly grown on the thin layer of rGO. The specific surface area of the aerogel and its rich pore structure inhibited aggregation and accumulation of the nanoparticles. Moreover, this structure facilitated the formation of a P–N heterogeneous structure, which ultimately enabled successful detection of hydrogen (H2) at room temperature. The sensitivity for 10 000 ppm H2 at room temperature was 27.66, and detection was stable and reproducible. Most notably, the response and recovery times for H2 were as short as 11 and 13 seconds, respectively. The addition of a hydrogen-sensitive functional material to a reduced graphene oxide aerogel shows great promise for room temperature gas sensing. [ABSTRACT FROM AUTHOR]

The safety and sustainability of the nuclear industry have become the focus of attention; therefore, it is important to develop adsorbents with high selectivity and high adsorption capacity to remove thorium Th(IV) from nuclear waste liquid. In this paper, a new polyamide (PA) composite membrane with zeolitic imidazole skeleton-67 (ZIF-67) nanoparticles was prepared using a deep permeation method. The nanoparticles were synthesized in situ within the PA membrane pores and uniformly distributed within each membrane pore. Characterization analysis and adsorption performance tests were performed to further investigate the performance of the composite membranes for the removal of Th(IV) from the nuclear waste liquid. The prepared ZIF-67@PA novel microporous membrane adsorbent material has a higher adsorption capacity (703.59 mg g−1) and a shorter adsorption equilibrium time (50 min) compared to ZIF-67 material adsorbents for Th(IV) removal. This work is expected to provide an effective strategy for the efficient removal of radioactive thorium ions from wastewater. [ABSTRACT FROM AUTHOR]

Background and aims Methods Results Conclusions Nuclear protein testis (NUT) carcinoma (NC) is a rare and highly aggressive tumour characterised by chromosomal rearrangement of the nuclear protein testis family member 1 (NUTM1) gene, also known as the NUT gene. NC occurs mainly in the head and neck, mediastinum and lung. In general, primary NC in the oral cavity is extremely rare and reported sporadically.A total of 111 formalin‐fixed and paraffin‐embedded specimens of poorly differentiated oral and oropharyngeal tumours were collected from 10 hospitals. NUT protein IHC staining was performed on these samples, and fluorescence in‐situ hybridisation (FISH) and RNA sequencing detection were further carried out for NUT IHC‐positive cases.The expression of NUT protein in tumour cells was detected in five cases (five of 111, 4.5%). The tumours in these cases were located in the oral floor, lip, base of the tongue, gingiva and hard palate. FISH detection results showed BRD4::NUT rearrangement in three patients and a non‐BRD4::NUT rearrangement pattern in two patients. RNA sequencing results confirmed BRD4::NUT rearrangement in two cases.To our knowledge, this is the first and largest retrospective study of oral NC, and we found that NC is easily misdiagnosed as poorly differentiated oral squamous cell carcinoma (SCC) or poorly differentiated carcinoma. The morphology and immunophenotype of four NC cases were similar to SCC, and abrupt keratinisation was observed in three cases. Therefore, it is necessary to detect NUT protein for NC screening in oral malignant tumours with these morphologies, especially for young patients who are more likely to be misdiagnosed with other types of cancer. [ABSTRACT FROM AUTHOR]

Odontogenic primary tumor is a rare benign odontogenic tumor in the maxillofacial area. A case of odontogenic primary basal tumor is reported. The clinicopathological features and treatment principles are discussed in the literature. [ABSTRACT FROM AUTHOR]