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Objectives The purpose of this study was to investigate the occurrence of labial bone perforation (LBP) and implantation into the maxillary sinus between various tooth-alveolar classifications with respect to the crown axis in maxillary premolars. Material and methods Cone beam computed tomography (CBCT) of 399 participants were analyzed to determine the probability of LBP and implantation into the maxillary sinus when associated with variables that included tooth position and tooth-alveolar classification. Results The morphology in the maxillary premolars was classified as straight, oblique, or boot-shaped. The first premolars were 62.3% straight, 37.0% oblique, and 0.8% boot-shaped and LBP occurred in 4.2% straight, 54.2% oblique, and 83.3% boot-shaped first premolars when the virtual implant was 3.5×10 mm. When the virtual implant was 4.3×10 mm, LBP occurred in 8.5% , 68.5% and 83.3% first premolars, respectively. The second premolars were 92.4% straight, 7.5% oblique, and 0.1% boot-shaped and LBP occurred in 0.5% straight , 33.3% oblique, and 0% boot-shaped, respectively, when the virtual implant was 3.5×10 mm; and LBP occurred in 1.3%, 53.3% and 100% second premolars, respectively, when the virtual implant was 4.3×10 mm. Conclusions When an implant is placed in the long axis of a maxillary premolar, the tooth position and tooth-alveolar classification should be considered when assessing the risk of LBP. Attention should be paid to the implant direction, diameter, and length in the oblique and boot-shaped maxillary premolars. Clinical relevance Preoperative CBCT needs to be used to reduce LBP in the maxillary premolars, especially when oblique or boot-shaped.

Concise and precise prognostic models are urgently needed due to the intricate genetic variations among hepatocellular carcinoma (HCC) cells. Disorder or change in glycolysis metabolism has been considered one of the "hallmarks" of cancer. However, the prognostic value of glycolysis-related genes in HCC remains elusive.A multigene prognostic model was constructed by least absolute shrinkage and selection operator Cox regression analysis in the The Cancer Genome Atlas (TCGA) cohort with 365 HCC patients and validated in the International Cancer Genome Consortium (ICGC) cohort with 231 HCC patients. The Kaplan-Meier methodology and time-dependent receiver operating characteristic curve were employed to confirm its predictive capability. A predictive nomogram was established based on the stepwise multivariate regression model. The differential expression of prognostic genes between HCC tissues and normal tissues was verified by quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry in an independent sample cohort with 30 HCC patients.The glycolysis-related gene signature and the nomogram model exhibited robust validity in predicting prognosis. The risk score was an independent predictor for overall survival (OS). Expression levels of immune checkpoint genes and cell cycle genes were significantly elevated in the high-risk group. The high-risk group presented high levels of immune exclusion. The risk score can distinguish the effect of immunotherapy in the IMvigor210 cohort. The prognostic gene expression showed a significant difference between HCC tissues and adjacent nontumorous tissues in the independent sample cohort.The currently established glycolysis-related gene signature can accurately predict prognosis and reflect immune status, which may be a therapeutic alternative.

A novel Ag3VO4/CoWO4 p–n heterostructure was designed and prepared by an in situ growth method. The physicochemical properties were characterized by multiple techniques, and the photocatalytic performances in Cr(vi) reduction and TC degradation were also evaluated under visible-light irradiation.

A new dihydroanthracene-based photochromic ligand was developed to construct a photochromic luminescent coordination polymer as the first sensing application, which has resulted in an outstanding MnO4− sensor.

Supplemental Material for Metabolic Disease and Risk of Thyroid Disease: Evidence from the National Nurse Health Cohort in China by Peng Wang, Heli Zhang, Jing Wang, Ying Che, Lin Zhuo, Miao Yu, Xianjing Hu, Peitao Li, Rongmei Geng, Siyan Zhan, and Baohua Li in Biological Research For Nursing

Background To apply CBCT to investigate the anatomical relationship between the mandibular molar and alveolar bone, aimed to provide clinical guidelines for the design of implant restoration. Methods 201 CBCT data were reevaluated to measure height of the alveolar process (EF), width of the alveolar process (GH), width of the basal bone (IJ), the angle between the long axis of the first molar and the alveolar bone (∠a) and the angle between the long axis of the alveolar bone and basal bone (∠b). The angle and width were measured to determine the implant-prosthodontic classification of the morphology in the left lower first molar (36) and right lower first molar (46). All measurements were performed on the improved cross-sectional images. Results EF, GH and IJ were measured as (10.83 ± 1.31) mm, (13.93 ± 2.00) mm and (12.68 ± 1.96) mm for 36, respectively; and (10.87 ± 1.24) mm, (13.86 ± 1.93) mm and (12.60 ± 1.90) mm for 46, respectively. No statistical significance was observed in EF, GH, IJ, ∠a and ∠b between 36 and 46 (all P > 0.05). The morphology was divided into three categories including the straight (68.7–69.2%), oblique (19.9–20.4%) and concave types (11%). Each type was consisted of two subcategories. Conclusions The proposed classification could provide evidence for appropriate selection and direction design of the mandibular molar implant in clinical. The concave type was the most difficult to implant with the highest risk of lingual perforation. The implant length, width, direction required more attention.

Problem: The novel coronavirus disease 2019 (COVID-19) pandemic adversely affected the preparation of Malaysia’s National Health and Morbidity Survey for 2020 because conducting it would expose data collectors and participants to an increased risk of infection. Context: The survey is nationally representative and community based and is conducted by the Institute for Public Health, part of the National Institutes of Health, to generate health-related evidence and to support the Malaysian Ministry of Health in policymaking. Its planned scope for 2020 was the seroprevalence of communicable diseases such as hepatitis B and C. Action: Additional components were added to the survey to increase its usefulness, including COVID-19 seroprevalence and facial anthropometric studies to ensure respirator fit. The survey’s scale was reduced, and data collection was changed from including only face-to-face interviews to mainly self-administered and telephone interviews. The transmission risk to participants was reduced by screening data collectors before the survey and fortnightly thereafter, using standard droplet and contact precautions, ensuring proper training and monitoring of data collectors, and implementing other administrative infection prevention measures. Outcome: Data were collected from 7 August to 11 October 2020, with 5957 participants recruited. Only 4 out of 12 components of the survey were conducted via face-to-face interview. No COVID-19 cases were reported among data collectors and participants. All participants were given their hepatitis and COVID-19 laboratory test results; 73 participants with hepatitis B and 14 with hepatitis C who had been previously undiagnosed were referred for further case management. Discussion: Preparing and conducting the National Health and Morbidity Survey during the COVID-19 pandemic required careful consideration of the risks and benefits, multiple infection prevention measures, strong leadership and strong stakeholder support to ensure there were no adverse events.

Introduction: The rapid spread of the COVID-19 worldwide has led the World Health Organization (WHO) to declare COVID-19 outbreak as a pandemic on March 11, 2020. This study aims to determine the factors associated with asymptomatic COVID-19 patients in Petaling District, Selangor, Malaysia. Methods: Data on COVID-19 patients were extracted from the database of confirmed cases in Petaling District Health Office, Selangor, Malaysia from 3rd February 2020 to 30th April 2020. An asymptomatic laboratory-confirmed case is a person infected with COVID-19 who does not develop any symptoms. The study included socio-demographic variables, the detailed information on clinical manifestations and co-morbidity of the patients. Descriptive and multivariable logistic regression analyses were conducted to determine the factors associated with asymptomatic patients. Results: The overall COVID-19 patients in Petaling District were 434. Approximately 70% (N = 292) of the patients were symptomatic while 32.7% (N = 142) were asymptomatic. Multivariable logistic regression analyses revealed that factors significantly associated with asymptomatic patients were age below 40 years old (aOR: 1.79, 95% CI 1.11, 2.86), non-Malaysians (aOR: 3.22, 95% CI 1.44, 7.19) and local cases (aOR: 2.51, 95% CI 1.42, 4.42). Gender, ethnicity, co-morbidity and township were not significantly associated with asymptomatic patients. Conclusion: Approximately one-third of COVID-19 patients were asymptomatic and the risk factors identified were younger age, non-Malaysians and local cases. Rigorous epidemiological investigation and laboratory examinations are helpful in identifying COVID-19 cases among these group of people who are asymptomatic. Keywords: COVID-19 - asymptomatic - pandemic - Malaysia

Immunity plays an important role in tumor development. In this study, we aimed to investigate molecular classification and its prognostic value in hepatocellular carcinoma (HCC) based on immune signature. Gene set enrichment analysis (GSEA) was used to calculate scores of immune pathways for HCC and hierarchical clustering in two databases (The Cancer Genome Atlas [TCGA], Liver Cancer-RIKEN, JP [LIRI_JP]). The scores of the immune microenvironment and the proportions of 22 immune cells were also calculated. Single-sample GSEA (ssGSEA) was used to screen survival prognosis-related immune pathways and calculate the hazard radio of differentially expressed immune-related genes (IRGs), which were validated in clinical samples and multiple datasets. Based on the immune characteristics, we identified three HCC subtypes, namely immunity high (Immunity_H), immunity medium (Immunity_M), and immunity low (Immunity_L), and confirmed that the classification was reliable and predictable. Immunity_H with a higher immune and stromal score indicated better survival rate. Cox regression analysis showed that IL18RAP and IL7R were the protective genes. Immune risk score was the independent risk factor of overall survival in HCC patients. These results indicated that immunogenomic classification could distinguish HCC patients with different immune status, which could impact the prognosis of the patients with HCC., Graphical abstract, Weiwei et al. provided an immunogenomic classification based on immune characteristics to distinguish hepatocellular carcinoma (HCC) patients with different immune status, and the prediction model can be used for individual immunotherapy of HCC patients.

Beer potomania is one of the less common causes of hyponatremia that we encounter. Patients usually have a recent history of binge drinking along with poor diet. The low solute content in alcoholic beverages limits daily urine output, and ingestion of extra fluid will cause dilutional hyponatremia as a result. Blindly providing intravenous fluid without an underlying cause of the hyponatremia can be detrimental, such as in patients with beer potomania. In our case, a patient presented to the emergency department due to poor oral intake from jaw pain and was found to be hyponatremic from alcohol intake. He initially received 2 liters of fluid, which caused overcorrection of his sodium, requiring more free water to lower his sodium as a result.

In present work, the CdS nanoparticle decorated ZnO porous nanosheets (CdS NP/ZnO PNs) were successfully synthesized through a facile wet-chemistry method. The as-prepared samples were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy and energy dispersive spectrum. The results proved the porous and monocrystalline structures of the ZnO nanosheets. A huge number of tiny CdS nanoparticles evenly cover the surface of the ZnO porous nanosheets, and the average size of the CdS nanoparticles is about 5 nm. The CdS NP/ZnO PNs exhibit excellent sensing activity and selectivity towards isopropanol. The linear response range is 1–100 ppm under the optimized operation temperature of 320 °C, and the detection limit is 1 ppm. The sensing performance of the CdS NP/ZnO PNs towards isopropanol is dramatically higher than that of other VOC gases, indicating the high selectivity to isopropanol. The CdS NP/ZnO PNs based sensor even can distinguish isopropanol from the complex mixed gases. Besides, the responses of the as-prepared sample to isopropanol seldom changed within 15 days. It is believed that the CdS NP/ZnO PNs have great application potential in isopropanol detection.

As a class of widely used biocatalysts, enzymes possess advantages including high catalytic efficiency, strong specificity and mild reaction condition. However, most free enzymes have high requirements on the reaction environment and are easy to deactivate. Immobilization of enzymes on nanomaterial-based substrates is a good way to solve this problem. Metal-organic framework (MOFs), with ultra-high specific surface area and adjustable porosity, can provide a large space to carry enzymes. And the tightly surrounded protective layer of MOFs can stabilize the enzyme structure to a great extent. In addition, the unique porous network structure enables selective mass transfer of substrates and facilitates catalytic processes. Therefore, these enzyme-immobilized MOFs have been widely used in various research fields, such as molecule/biomolecule sensing and imaging, disease treatment, energy and environment protection. In this review, the preparation strategies and applications of enzyme-immobilized MOFs are illustrated and the prospects and current challenges are discussed.

Background There is presently no effective and safe vaccine for Toxoplasma gondii for humans. The study described here was designed to search for a novel group of optimal B cell and T cell epitopes from Toxoplasma membrane proteins using genome-wide comprehensive screening. Methods The amino acid sequences of membrane proteins of T. gondii were obtained from the UniProt database. The ABCPred and BepiPred servers were employed to predict the linear B cell epitopes. The Immune Epitope Database (IEDB) online service was utilized to forecast T cell epitopes within T. gondii membrane proteins that bind to human leukocyte antigen (HLA) class I (HLA-I) or HLA-II molecules. Results From the 314 membrane proteins of T. gondii, a total of 14 linear B cell epitopes embedded in 12 membrane proteins were identified. Eight epitopes for major histocompatibility complex (MHC) class I (MHC-I) molecules and 18 epitopes for MHC-II molecules were ultimately selected, for which world population coverage percentiles were 71.94% and 99.76%, respectively. The top rated combinations of linear B cell epitopes and T cell epitopes covering both BALB/c mice and a majority of the human population were identified for the development of a protective vaccine. Conclusions The ultimate vaccine construct described here, which comprises B cells, MHC-I and MHC-II epitopes, might protect individuals against T. gondii infection by inducing humoral and cellular immune responses. Graphic abstract

Heteroatom doping was recently regarded as an effective method to tune the band gap and improve the separation and transfer of photogenerated electron-hole pairs in semiconductor photocatalysts. Herein, a novel S,F-codoped Bi