Assessing risk of recurrent small bowel obstruction after non-operative management in patients with history of intra-abdominal surgery: a population-based comprehensive analysis in Taiwan.

BACKGROUND: Despite a significant 30% ten-year readmission rate for SBO patients, investigations into recurrent risk factors after non-operative management are scarce. The study aims to generate a risk factor scoring system, the 'Small Bowel Obstruction Recurrence Score' (SBORS), predicting 6-month recurrence of small bowel obstruction (SBO) after successful non-surgical management in patients who have history of intra-abdominal surgery. METHODS: We analyzed data from patients aged ≥ 18 with a history of intra-abdominal surgery and diagnosed with SBO (ICD-9 code: 560, 568) and were successful treated non-surgically between 2004 and 2008. Participants were divided into model-derivation (80%) and validation (20%) group. RESULTS: We analyzed 23,901 patients and developed the SBORS based on factors including the length of hospital stay > 4 days, previous operations > once, hemiplegia, extra-abdominal and intra-abdominal malignancy, esophagogastric surgery and intestino-colonic surgery. Scores > 2 indicated higher rates and risks of recurrence within 6 months (12.96% vs. 7.27%, OR 1.898, p < 0.001 in model-derivation group, 12.60% vs. 7.05%, OR 1.901, p < 0.001 in validation group) with a significantly increased risk of mortality and operative events for recurrent episodes. The SBORS model demonstrated good calibration and acceptable discrimination, with an area under curve values of 0.607 and 0.599 for the score generation and validation group, respectively. CONCLUSIONS: We established the effective 'SBORS' to predict 6-month SBO recurrence risk in patients who have history of intra-abdominal surgery and have been successfully managed non-surgically for the initial obstruction event. Those with scores > 2 face higher recurrence rates and operative risks after successful non-surgical management.

Efficacy of Adjuvant Sublingual Immunotherapy After Septomeatoplasty.

BACKGROUND: The efficacy of adjuvant sublingual immunotherapy (SLIT) in correcting structural problems in patients with allergic rhinitis (AR) caused by mite who have undergone septomeatoplasty (SMP) has not been studied. METHODS: This non-randomized controlled study recruited patients with AR (caused by mite) and concurrent septal deviation and inferior turbinate hypertrophy, at a tertiary hospital in Taiwan. SMP was performed on all patients as a surgical intervention. The patients were then divided into two groups: the control group, which underwent surgery only, and the experimental group, which received SLIT as an adjuvant treatment. Demographic data and rhinitis control assessment test (RCAT) results were analyzed. RESULTS: A total of 96 patients were enrolled in the study (SMP + SLIT group, n = 52; SMP only group, n = 44). No significant differences were observed in any of the variables between the two groups before and one month after surgery. However, during evaluations at the third and sixth month, the SMP + SLIT group showed significant improvement in the total RCAT scores compared to the SMP only group (28.6 ± 1.56 vs. 24.5 ± 3.66, p < 0.001; 27.1 ± 2.87 vs. 19.9 ± 5.56, p < 0.001). In addition, significantly better control of all RCAT sub-categories was observed in the SMP + SLIT group at the third and sixth month evaluations. CONCLUSIONS: SLIT may serve as an ideal adjuvant therapy after SMP in patients with AR. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:3073-3079, 2024.

Composition design and optimization of Fe-C-Mn-Al steel based on machine learning.

The purpose of this study is to explore the composition space of Fe-C-Mn-Al steel using machine learning in order to identify materials with high-strength mechanical properties. A dataset of 580 steel samples was collected from the literature, each containing information on elemental composition, heat treatment processes, specimen dimensions, and mechanical properties (ultimate tensile strength and total elongation). Eight common machine learning models were constructed to predict the ultimate tensile strength (UTS) and total elongation (TE) of the steel. It was observed that the random forest regression (RFR) model, when trained, demonstrated superior overall performance in predicting UTS, with an average absolute error of approximately 90 MPa, and TE, with an average absolute error of about 7.9%. Validation of the model using eight sets of data that were not part of the dataset revealed that the predictions were in close agreement with experimental results, indicating the strong predictive capability of the RFR model. Subsequently, the trained RFR model was used to explore the composition space of Fe-C-Mn-Al steel, identifying the top fifty combinations of elemental compositions and heat treatment parameters, all of which manifest high ultimate tensile strength (UTS). This provides valuable research directions and methods to expedite the development of high-strength Fe-C-Mn-Al steel.

Size-selective adhesion of calcium oxalate monohydrate crystals to lipid membranes.

The retention of calcium oxalate monohydrate (COM) crystals on cell membranes is pivotal in kidney stone formation. However, the mechanisms underlying COM attachment to neutral lipid membranes remain unclear. In this study, we demonstrate that COM exhibits size-selective adhesion to fluid lipid membranes composed of lipids with distinct sizes. Specifically, the (100) facet of COM induces the formation of new domains and establishes strong adhesion in the 18:1 (Δ9-Cis) PC (DOPC) membrane, while the (010) facet induces domains with strong adhesion in the 16:0-14:0 PC membrane. This selectivity is linked to the compatibility of the area per lipid in DOPC with the unit cell area of the (100) facet and the area per lipid in 16:0-14:0 PC with the (010) facet. Our Raman spectroscopic analyses reveal that the lipid acyl chains within these induced domains exhibit a higher degree of ordering compared to the typical fluid state of the membrane. This ordered structural alignment, combined with the lateral size-matching effect, suggests the potential formation of molecular arrays within the lipid bilayer that are in harmony with the lattice dimension of COM. To elucidate the strong adhesion between calcium oxalate and the phospholipid head group in the absence of a direct molecular structural correspondence, we propose that crystal water associated with COM can form hydrogen bonds with the phospholipid head group. Using structure visualization software, we demonstrate the feasibility of such hydrogen bonding networks. The formation of this network could serve to stabilize and enhance the attachment of COM to the lipid membrane. This mediation by water molecules offers a plausible explanation for the pronounced affinity at the interface.

Reliability of predicting low-burden (≤ 2) positive axillary lymph nodes indicating sentinel lymph node biopsy in primary operable breast cancer - a retrospective comparative study with PET/CT and breast MRI.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is the standard of care for axillary staging in early breast cancer patients with low-burden axillary metastasis (≤ 2 positive nodes). This study aimed to determine the diagnostic performances of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and breast magnetic resonance imaging in detecting axillary lymph node (ALN) metastases and the reliability to predict ALN burden. METHODS: A total of 275 patients with primary operable breast cancer receiving preoperative PET/CT and upfront surgery from January 2001 to December 2022 in a single institution were enrolled. A total of 244 (88.7%) of them also received breast MRI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PET/CT and breast MRI were assessed. The predictive values to determine ALN burden were evaluated using radio-histopathological concordance. RESULTS: PET/CT demonstrated a sensitivity of 53.4%, specificity of 82.1%, PPV of 65.5%, NPV of 73.5%, and accuracy of 70.9% for detecting ALN metastasis, and the corresponding values for MRI were 71.8%, 67.8%, 56%, 80.8%, and 69.2%, respectively. Combining PET/CT and MRI showed a significantly higher PPV than MRI (72.7% vs 56% for MRI alone, p = 0.037) and a significantly higher NPV than PET/CT (84% vs 73.5% for PET/CT alone, p = 0.041). For predicting low-burden axillary metastasis (1-2 positive nodes), the PPVs were 35.9% for PET/CT, 36.7% for MRI, and 55% for combined PET/CT and MRI. Regarding patients with 0-2 positive ALNs in imaging, who were indicated for SLNB, the predictive correctness was 96.1% for combined PET/CT and MRI, 95.7% for MRI alone, and 88.6% for PET/CT alone. CONCLUSIONS: PET/CT and breast MRI exhibit high predictive values for identifying low-burden axillary metastasis in patients with operable breast cancer with ≦ 2 positive ALNs on imaging.

Effects of surface treatments of bioactive tricalcium silicate-based restorative material on the bond strength to resin composite.

OBJECTIVES: This study aimed to enhance the bond strength between Biodentine™ (BD), a bioactive tricalcium silicate (C3S) based material, and resin composite through various surface treatments. METHODOLOGY: BD samples were immersed in either double distilled water or Hank's Balanced Salt Solution and analyzed using X-ray Diffraction (XRD). Shear bond strength (SBS) evaluations of BD were performed using Prime & Bond™ NT (PNT), Single Bond Universal (SBU), Xeno V (Xeno), and glass ionomer cement (GIC) following various etching durations (0 s/ 15 s/ 30 s/ 60 s with 37.5% phosphoric acid). Two primers, RelyX™ Ceramic Primer (RCP) and Monobond ™ Plus (MBP), were chosen to prime BD for SBS enhancement. Fractography and bonding interfaces were examined with energy dispersive X-ray spectroscopy (EDS)/ scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). RESULTS: XRD confirmed BD's main compositions as C3S, Ca(OH)2, CaCO3 and ZrO2 after 14 days crystal maturation. Etched BD did not improve SBS. GIC exhibited the lowest SBS (p < 0.05) among all adhesives, regardless of the etching mode (all < 1 MPa). The highest SBS (17.5 ± 3.6 MPa, p < 0.05) was achieved when BD primed with MBP followed by SBU application. FTIR and EDS showed γ-MPTS and10-MDP within the MBP primer interacted with C3S and ZrO2 of BD, achieving enhanced SBS. Most specimens exhibited mixed or cohesive failure modes. Significance BD's subpar mechanical properties and texture may contribute to its poor adhesion to resin composite. Pretreating BD with MBP primer, followed by SBU adhesive is recommended for improving bond strength.

Deep convolutional neural network with fusion strategy for skin cancer recognition: model development and validation.

We aimed to develop an accurate and efficient skin cancer classification system using deep-learning technology with a relatively small dataset of clinical images. We proposed a novel skin cancer classification method, SkinFLNet, which utilizes model fusion and lifelong learning technologies. The SkinFLNet's deep convolutional neural networks were trained using a dataset of 1215 clinical images of skin tumors diagnosed at Taichung and Taipei Veterans General Hospital between 2015 and 2020. The dataset comprised five categories: benign nevus, seborrheic keratosis, basal cell carcinoma, squamous cell carcinoma, and malignant melanoma. The SkinFLNet's performance was evaluated using 463 clinical images between January and December 2021. SkinFLNet achieved an overall classification accuracy of 85%, precision of 85%, recall of 82%, F-score of 82%, sensitivity of 82%, and specificity of 93%, outperforming other deep convolutional neural network models. We also compared SkinFLNet's performance with that of three board-certified dermatologists, and the average overall performance of SkinFLNet was comparable to, or even better than, the dermatologists. Our study presents an efficient skin cancer classification system utilizing model fusion and lifelong learning technologies that can be trained on a relatively small dataset. This system can potentially improve skin cancer screening accuracy in clinical practice.

Keystroke Biometrics as a Tool for the Early Diagnosis and Clinical Assessment of Parkinson's Disease.

(1) Background: Parkinson's disease (PD) is the second most common neurodegenerative disease. Early diagnosis and reliable clinical assessments are essential for appropriate therapy and improving patients' quality of life. Keystroke biometrics, which capture unique typing behavior, have shown potential for early PD diagnosis. This study aimed to evaluate keystroke biometric parameters from two datasets to identify indicators that can effectively distinguish de novo PD patients from healthy controls. (2) Methods: Data from natural typing tasks in Physionet were analyzed to estimate keystroke biometric parameters. The parameters investigated included alternating-finger tapping (afTap) and standard deviations of interkey latencies (ILSD) and release latencies (RLSD). Sensitivity rates were calculated to assess the discriminatory ability of these parameters. (3) Results: Significant differences were observed in three parameters, namely afTap, ILSD, and RLSD, between de novo PD patients and healthy controls. The sensitivity rates were high, with values of 83%, 88%, and 96% for afTap, ILSD, and RLSD, respectively. Correlation analysis revealed a significantly negative correlation between typing speed and number of words typed with the standard motor assessment for PD, UPDRS-III, in patients with early PD. (4) Conclusions: Simple algorithms utilizing keystroke biometric parameters can serve as effective screening tests in distinguishing de novo PD patients from healthy controls. Moreover, typing speed and number of words typed were identified as reliable tools for assessing clinical statuses in PD patients. These findings underscore the potential of keystroke biometrics for early PD diagnosis and clinical severity assessment.

Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using ConnecTF.

Many methods are now available to identify or predict the target genes of transcription factors (TFs) in plants. These include experimental approaches such as in vivo or in vitro TF-target gene-binding assays and various methods for identifying regulated targets in mutants, transgenics, or isolated plant cells. In addition, computational approaches are used to infer TF-target gene interactions from the regulatory elements or gene expression changes across treatments. While each of these approaches has now been applied to a large number of TFs from many species, each method has its own limitations which necessitates that multiple data types are integrated to build the most accurate representation of the gene regulatory networks operating in plants. To make the analyses of TF-target interaction datasets available to the broader research community, we have developed the ConnecTF web platform ( https://connectf.org/ ). In this chapter, we describe how ConnecTF can be used to integrate validated and predicted TF-target gene interactions in order to dissect the regulatory role of TFs in developmental and stress response pathways. Using as our examples KN1 and RA1, two well-characterized maize TFs involved in developing floral tissue, we demonstrate how ConnecTF can be used to (1) compare the target genes between TFs, (2) identify direct vs. indirect targets by combining TF-binding and TF-regulation datasets, (3) chart and visualize network paths between TFs and their downstream targets, and (4) prune inferred user networks for high-confidence predicted interactions using validated TF-target gene data. Finally, we provide instructions for setting up a private version of ConnecTF that enables research groups to store and analyze their own TF-target gene interaction datasets.

Using the Water Absorption Ability of Dried Hydrogels to Form Hydrogel-Supported Lipid Bilayers.

The formation of supported lipid bilayers (SLBs) on hydrogels can act as a biocompatible anti-fouling interface. However, generating continuous and mobile SLBs on materials other than conventional glass or mica remains a significant challenge. The interaction between lipid membrane vesicles and a typical hydrogel is usually insufficient to induce membrane vesicle rupture and form a planar lipid membrane. In this study, we demonstrate that the water absorption ability of a dried polyacrylamide (PAAm) hydrogel could serve as a driving force to facilitate the formation of the hydrogel-SLBs. The absorption driving force vanishes after the hydrogels are fully hydrated, leaving no extra interaction hindering lipid lateral mobility in the formed SLBs. Our fluorescence recovery after photobleaching (FRAP) results show that SLBs only form on hydrogels with adequate absorption abilities. Moreover, we discovered that exposure to oxygen during drying could lead to the formation of an oxidized crust on the PAAm hydrogel surface, impeding SLB formation. Therefore, minimizing oxygen exposure during drying is crucial to achieving high-quality hydrogel surfaces for SLB formation. This water absorption method enables the straightforward fabrication of hydrogel-SLBs without the need for additional substrates or charges, thereby expanding their potential applications.

Diagnostic accuracy of pre-operative breast magnetic resonance imaging (MRI) in predicting axillary lymph node metastasis: variations in intrinsic subtypes, and strategy to improve negative predictive value-an analysis of 2473 invasive breast cancer patients.

BACKGROUND: The value and utility of axillary lymph node (ALN) evaluation with MRI in breast cancer were not clear for various intrinsic subtypes. The aim of the current study is to test the potential of combining breast MRI and clinicopathologic factors to identify low-risk groups of ALN metastasis and improve diagnostic performance. MATERIAL AND METHODS: Patients with primary operable invasive breast cancer with pre-operative breast MRI and post-operative pathologic reports were retrospectively collected from January 2009 to December 2021 in a single institute. The concordance of MRI and pathology of ALN status were determined, and also analyzed in different intrinsic subtypes. A stepwise strategy was designed to improve MRI-negative predictive value (NPV) on ALN metastasis. RESULTS: 2473 patients were enrolled. The diagnostic performance of MRI in detecting metastatic ALN was significantly different between intrinsic subtypes (p = 0.007). Multivariate analysis identified tumor size and histologic type as independent predictive factors of ALN metastases. Patients with HER-2 (MRI tumor size ≤ 2 cm), or TNBC (MRI tumor size ≤ 2 cm) were found to have MRI-ALN-NPV higher than 90%, and these false cases were limited to low axillary tumor burden. CONCLUSION: The diagnostic performance of MRI to predict ALN metastasis varied according to the intrinsic subtype. Combined pre-operative clinicopathologic factors and intrinsic subtypes may increase ALN MRI NPV, and further identify some groups of patients with low risks of ALN metastasis, high NPV, and low burdens of axillary disease even in false-negative cases.

Non-Homologous End-Joining Pathway Genotypes Significantly Associated with Nasopharyngeal Carcinoma Susceptibility.

Defects in the non-homologous end-joining (NHEJ) DNA repair pathway lead to genomic instability and carcinogenesis. However, the roles of individual NHEJ genes in nasopharyngeal carcinoma (NPC) etiology are not well-understood. The aim of this study was to assess the contribution of NHEJ genotypes, including XRCC4 (rs6869366, rs3734091, rs28360071, rs28360317, rs1805377), XRCC5 (rs828907, rs11685387, rs9288518), XRCC6 (rs5751129, rs2267437, rs132770, rs132774), XRCC7 rs7003908, and Ligase4 rs1805388, to NPC risk, with 208 NPC patients and 416 controls. Genotype-phenotype correlations were also investigated by measuring mRNA and protein expression in adjacent normal tissues and assessing the NHEJ repair capacity in blood lymphocytes from 43 NPC patients. The results showed significant differences in the distributions of variant genotypes at XRCC4 rs3734091, rs28360071, and XRCC6 rs2267437 between the cases and controls. The variant genotypes of these three polymorphisms were associated with significantly increased NPC risks. NPC patients with the risk genotypes at XRCC6 rs2267437 had significantly reduced expression levels of both mRNA and protein, as well as a lower NHEJ repair capacity, than those with the wild-type genotype. In conclusion, XRCC4 rs3734091, rs28360071, and XRCC6 rs2267437 in the NHEJ pathway were associated with NPC susceptibility. XRCC6 rs2267437 can modulate mRNA and protein expression and the NHEJ repair capacity.

The classification of stages of epiretinal membrane using convolutional neural network on optical coherence tomography image.

BACKGROUND AND OBJECTIVE: The gold standard for diagnosing epiretinal membranes is to observe the surface of the internal limiting membrane on optical coherence tomography images. The stages of the epiretinal membrane are used to decide the condition of the health of the membrane. The stages are not detected because some of them are similar. To accurately classify the stages, a deep-learning technology can be used to improve the classification accuracy. METHODS: A combinatorial fusion with multiple convolutional neural networks (CNN) algorithms are proposed to enhance the accuracy of a single image classification model. The proposed method was trained using a dataset of 1947 optical coherence tomography images diagnosed with the epiretinal membrane at the Taichung Veterans General Hospital in Taiwan. The images consisted of 4 stages; stages 1, 2, 3, and 4. RESULTS: The overall accuracy of the classification was 84%. The combination of five and six CNN models achieves the highest testing accuracy (85%) among other combinations, respectively. Any combination with a different number of CNN models outperforms any single CNN algorithm working alone. Meanwhile, the accuracy of the proposed method is better than ophthalmologists with years of clinical experience. CONCLUSIONS: We have developed an efficient epiretinal membrane classification method by using combinatorial fusion with CNN models on optical coherence tomography images. The proposed method can be used for screening purposes to facilitate ophthalmologists making the correct diagnoses in general medical practice.

Association of EZH2 Genotypes With Oral Cancer Risk.

BACKGROUND/AIM: The over-expression of enhancer of zeste homolog 2 (EZH2) protein is found in oral cancer tissues. However, the genetic role of the enhancer of EZH2 in the etiology of oral cancer is unknown. The aim of this study was to evaluate the association of EZH2 genotypes with oral cancer risk among Taiwanese. MATERIALS AND METHODS: Three polymorphic variants of EZH2, rs887569 (C to T), rs41277434 (A to C), and rs3757441 (T to C), were analyzed regarding their association with oral cancer risk among 958 oral cancer patients and the same number of healthy controls by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). In addition, the interaction of EZH2 rs887569, rs41277434, and rs3757441 genotypes with personal behaviors such as smoking, alcohol drinking, and betel quid chewing were also examined. RESULTS: The EZH2 genotypes rs887569, rs41277434, and rs3757441, were not significantly associated with oral cancer risk (p for trend=0.1735, 0.5658, and 0.4606, respectively). The analysis of allelic frequency distribution also supported the findings that the variant alleles at EZH2 rs887569, rs41277434, and rs3757441 may not serve as determinants of oral cancer risk (all p>0.05). There was no interaction between EZH2 rs887569, rs41277434, or rs3757441 genotypes with personal smoking, alcohol drinking or betel quid chewing behaviors. CONCLUSION: EZH2 genotypes cannot predict oral cancer risk in Taiwan.

The Contribution of Flap Endonuclease 1 Genotypes to Oral Cancer Risk.

BACKGROUND/AIM: Flap endonuclease 1 (FEN1) is a critical protein in DNA repair, genomic stability, and carcinogenesis. Functional polymorphisms in FEN1 promoter -69G>A (rs174538) and 3'UTR 4150G>T (rs4246215), have been associated with the susceptibility to several cancers, including lung, breast, esophageal, gastric, liver, colorectal, and gallbladder cancer, as well as glioma, endometriosis, and leukemia. However, the contribution of FEN1 variant genotypes to oral cancer has never been examined. Thus, we aimed to evaluate the contribution of FEN1 rs174538 and rs4246215 genotypes to oral cancer risk in Taiwan. MATERIALS AND METHODS: The contribution of FEN1 genotypes to oral cancer risk was examined in 958 oral cancer patients and 958 age- and sex-matched healthy controls by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). RESULTS: The percentages of GG, AG, and AA genotypes at FEN1 rs174538 were 34.8%, 46.0%, and 19.2% among oral cancer patients and 37.8%, 45.2%, and 17.0% among healthy controls (p for trend=0.2788). The genotypic percentages of FEN1 rs4246215 were 35.9%, 45.9%, and 18.2% among oral cancer patients and 37.6%, 45.1%, and 17.3% among healthy controls (p for trend=0.7315). Overall, FEN1 rs174538 and rs4246215 were not differently distributed between the oral cancer patient and healthy control groups. The allele frequency analysis confirmed that FEN1 rs174538 and rs4246215 were non-differentially distributed among case and control groups (OR=1.11 and 1.05, 95%CI=0.98-1.27 and 0.93-1.20, p=0.1074 and 0.4491, respectively). CONCLUSION: FEN1 may contribute to oral cancer risk determination via protein expression and/or post-transcription modification, but may not be a practical genetic marker.

Multiple growth factors accommodated degradable submicron calcium sulfate hemihydrate/porous hydroxyapatite for dentin-pulp regeneration.

Vital pulp therapy (VPT) has gained significant consideration by utilizing the natural healing capacity of the inflamed pulp in healing process. However, the protective pulp capping materials that facilitate this healing process are still under investigation for the successful promotion of dentin-pulp regeneration. Herein, we developed a bioactive and biodegradable pulp capping material (denoted as sCSHA-GFs) by synthesizing inorganic submicron calcium sulfate hemihydrate (sCS)/porous hydroxyapatite (HA) loaded with growth factors (GFs) such as transforming growth factor-beta 1 (TGF-ß1), fibroblast growth factor-2 (FGF-2) and vascular endothelial growth factor (VEGF). Physiochemical characteristics of submicron CSHA-GFs (sCSHA-GFs) cement were determined. Human dental pulp stem cells (hDPSCs) were used for analyzing their biocompatibility and bioactivity for dentin mineralization. To evaluate the efficacy of sCSHA-GFs, we compared it with a commercial material, mineral trioxide aggregate (MTA), the reference standard used clinically on pulp capping. Our results showed that sCSHA-GFs cement presented good biodegradability with dissolution properties for sustained release of calcium (Ca2+) ions and GFs, and facilitated attachment, proliferation, differentiation and migration of hDPSCs. In addition, sCSHA-GFs cement was found to be more effective than MTA at prolonged incubation time in inducing the mRNA expression levels of odontoblastic differentiation markers, dentin sialophosphoprotein (DSPP) and dentin matrix protein (DMP-1), leading to increased mineralization (with calcium deposits) along with increased alkaline phosphatase (ALP) expressions, evident from Alizarin Red S and ALP staining assays. Our findings suggest that sCSHA-GFs cement may act as a suitable material in VPT for dentin-pulp regeneration.

Stable carbon isotopic characterization of rice vinegar protein as an intrinsic reference for discriminating the authenticity of brewed rice vinegar.

Rice vinegar plays an important role in daily life. However, some unscrupulous manufacturers may deliberately add synthetic acetic acid in vinegar products to reduce fermentation time and save production costs. To protect the rights and health of consumers, vinegar authenticity must be controlled. The rice vinegar protein was used as an intrinsic reference and its stable carbon isotope ratio (δ13Cprotein) was analyzed by elemental analyzer-isotope ratio mass spectrometry. The stable carbon isotope ratio difference between the acetic acid and the rice vinegar protein (Δδ13Cacetic acid-protein) was calculated to evaluate vinegar authenticity. Sixteen rice vinegar samples were analyzed and a stable carbon isotopic pattern of rice vinegar was established by the 95% confidence interval for Δδ13Cacetic acid-protein (0.27‰-2.10‰). An acetic acid adulteration curve of Δδ13Cacetic acid-protein was also assumed according to the data from rice vinegar samples, and its validity was confirmed by rice vinegar deliberately blended with acetic acid at different ratios (25, 50, and 75%). The Δδ13Cacetic acid-protein values of the adulterated vinegars decreased with increasing amounts blended acetic acid, but the δ13Cprotein values did not, showing that rice vinegar protein could be used as an intrinsic reference for identifying the adulterated rice vinegar. The rice vinegar adulterated with acetic acid at higher than approximately 10% could be detected.

The Contribution of PDCD6 Polymorphisms to Oral Cancer Risk.

BACKGROUND/AIM: Programmed cell death 6 (PDCD6) is up-regulated and highly expressed in early apoptotic cells. In several types of cancer, such as cervical, breast and lung cancers, the association of PDCD6 genotypes have been investigated. However, the contribution of PDCD6 variant genotypes to oral cancer has never been examined. The current study aimed to evaluate the contribution of the PDCD6 rs4957014 and rs3756712 genotypes to the risk of oral cancer in Taiwan. PATIENTS AND METHODS: The contribution of PDCD6 genotypes to oral cancer risk was examined among 958 patients with lung cancer and 958 age- and sex-matched healthy controls by polymerase chain reaction-restriction fragment length polymorphism (PCR- RFLP). RESULTS: The data showed that the hetero-variant GT and homo-variant GG genotypes of PDCD6 rs4957014 were associated with a decreased risk of oral cancer [odds ratio (OR)=0.81 and 0.39, 95% confidence interval (CI)=0.67-0.97 and 0.27-0.56, respectively]. The recessive and dominant models also showed that G carriers have protective effects (OR=0.43 and 0.72, 95% CI=0.30-0.61 and 0.61-0.87, respectively). The analysis of allelic frequency distributions showed that the G allele of PDCD6 rs4957014 was associated with reduced oral cancer risk (OR=0.71, 95% CI=0.62-0.82). There was no significant association between any PDCD6 rs3756712 genotype and oral cancer risk. In addition, the GG genotype at PDCD6 rs4957014 significantly decreased the risk of oral cancer among both males (adjusted OR=0.31, 95%CI=0.24-0.56) and females (adjusted OR=0.44, 95% CI=0.22-0.91). Furthermore, the GG genotype at PDCD6 rs4957014 significantly decreased the risk of oral cancer among smokers (adjusted OR=0.35, 95% CI=0.22-0.58), alcohol drinkers (adjusted OR=0.33, 95% CI=0.18-0.49), non-betel quid chewers (adjusted OR=0.33, 95% CI=0.17- 0.81), betel quid chewers (adjusted OR=0.34, 95% CI=0.21- 0.59), but not among never-smokers and non-alcohol drinkers. CONCLUSION: The G allele carriers of PDCD6 rs4957014 may have protective effects on oral cancer risk and serve as a practical marker for early detection of oral cancer in Taiwan.

Atypical functional connectivity during rest and task-related dynamic alteration in young children with attention deficit hyperactivity disorder: An analysis using the phase-locking value.

AIM: The study investigated the electroencephalography (EEG) functional connectivity (FC) profiles during rest and tasks of young children with attention deficit hyperactivity disorder (ADHD) and typical development (TD). METHODS: In total, 78 children (aged 5-7 years) were enrolled in this study; 43 of them were diagnosed with ADHD and 35 exhibited TD. Four FC metrics, coherence, phase-locking value (PLV), pairwise phase consistency, and phase lag index, were computed for feature selection to discriminate ADHD from TD. RESULTS: The support vector machine classifier trained by phase-locking value (PLV) features yielded the best performance to differentiate the ADHD from the TD group and was used for further analysis. In comparing PLVs with the TD group at rest, the ADHD group exhibited significantly lower values on left intrahemispheric long interelectrode lower-alpha and beta as well as frontal interhemispheric beta frequency bands. However, the ADHD group showed higher values of central interhemispheric PLVs on the theta, higher-alpha, and beta bands. Regarding PLV alterations within resting and task conditions, left intrahemispheric long interelectrode beta PLVs declined from rest to task in the TD group, but the alterations did not differ in the ADHD group. Negative correlations were observed between frontal interhemispheric beta PLVs and the Disruptive Behavior Disorder Rating Scale as rated by teachers. CONCLUSIONS: These results, which complement the findings of other sparse studies that have investigated task-related brain FC dynamics, particularly in young children with ADHD, can provide clinicians with significant and interpretable neural biomarkers for facilitating the diagnosis of ADHD.

A review for cell and particle tracking on microscopy images using algorithms and deep learning technologies.

Time-lapse microscopy images generated by biological experiments have been widely used for observing target activities, such as the motion trajectories and survival states. Based on these observations, biologists can conclude experimental results or present new hypotheses for several biological applications, i.e. virus research or drug design. Many methods or tools have been proposed in the past to observe cell and particle activities, which are defined as single cell tracking and single particle tracking problems, by using algorithms and deep learning technologies. In this article, a review for these works is presented in order to summarize the past methods and research topics at first, then points out the problems raised by these works, and finally proposes future research directions. The contributions of this article will help researchers to understand past development trends and further propose innovative technologies.