Cu(II)-Mediated Sulfonylation of (Hetero)arenes with TosMIC Using Monodentate Directing Groups.

Monodentate chelation-assisted direct ortho-C-H sulfonylation of (hetero)arenes using TosMIC as the novel sulfonylating reagent has been developed. A broad range of substrates, including indolines, indoles, 2-phenylpyridines, and others were well tolerated to afford the corresponding products in moderate to good yields. Mechanistic studies revealed that the sulfonyl radical might be involved. Inspired by the above discovery, preliminary para-C-H sulfonylation of naphthalene substrate was also successfully realized. The current protocol featured with cheap metal catalysis, good functional group compatibility, and operational convenience.

AnWRKY29 and AnHSP90 synergistically modulate trehalose levels in a desert shrub leaves during osmotic stress.

Trehalose, a biological macromolecule with osmotic adjustment properties, plays a crucial role during osmotic stress. As a psammophyte, Ammopiptanthus nanus relies on the accumulation of organic solutes to respond to osmotic stress. We utilized virus-induced gene silencing technology for the first time in the desert shrub A. nanus to confirm the central regulatory role of AnWRKY29 in osmotic stress, as it controls the transcription of AnTPS11 (trehalose-6-phosphate synthase 11). Further investigation has shown that AnHSP90 may interact with AnWRKY29. The AnHSP90 gene is sensitive to osmotic stress, underscoring its pivotal role in orchestrating the response to such adverse conditions. By directly targeting the W-box element within the AnTPS11 promoter, AnWRKY29 effectively enhances the transcriptional activity of AnTPS11, which is facilitated by AnHSP90. This discovery highlights the critical role of AnWRKY29 and AnHSP90 in enabling organisms to adapt to and cope effectively with osmotic stress, which can be a crucial factor in A. nanus survival and overall ecological resilience. Collectively, uncovering the molecular mechanisms underlying the osmotic responses of A. nanus is paramount for comprehending and augmenting the osmotic tolerance mechanisms of psammophyte shrub plants.

Effects of mind-body exercise on knee osteoarthritis: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: To evaluate the effect of mind-body exercise on improving knee osteoarthritis (KOA) and thereby informing osteoarthritis exercise rehabilitation. METHODS: The China National Knowledge Infrastructure (CNKI), Wanfang, PubMed/Medline, Cochrane Library, Web of Science, EBSCO, Embase, Scopus, and ProQuest databases were searched to identify randomized controlled trials (RCTs) that involved tai chi, yoga, and baduanjin interventions for KOA. The search period ranged from inception to October 25, 2022. The methodological quality of the included studies was evaluated by the Cochrane risk of bias assessment tool, and the included data were statistically analyzed and plotted using Review Manager 5.3 and Stata 14.0 software. RESULTS: We included 17 articles with a total of 1122 patients. Compared with the control group, mind-body exercise significantly improved patient pain (standardized mean difference (SMD) = -0.65, 95% confidence interval (CI) [-0.87, -0.42], p < 0.00001), stiffness (SMD = -0.75, 95% CI [-1.05, -0.45], p < 0.00001), physical function (SMD = -0.82, 95% CI [-1.03, -0.62], p < 0.00001), mental health (SMD = 0.31, 95% CI [0.11, 0.51], p = 0.002), and depression (SMD = -0.32, 95% CI [-0.50, -0.15], p = 0.0003). In terms of motor ability, mind-body exercise significantly increased the 6-min walking distance (SMD = 18.45, 95% CI [5.80, 31.10], p = 0.004) and decreased timed up and go test time (SMD = -1.15, 95% CI [-1.71, -0.59], p < 0.0001). CONCLUSIONS: The current study showed that mind-body exercise is safe and effective for KOA patients. However, given the methodological limitations of the included studies, additional high-quality evidence is needed to support the conclusions of this study.

Predicting quetiapine dose in patients with depression using machine learning techniques based on real-world evidence.

BACKGROUND: Being one of the most widespread, pervasive, and troublesome illnesses in the world, depression causes dysfunction in various spheres of individual and social life. Regrettably, despite obtaining evidence-based antidepressant medication, up to 70% of people are going to continue to experience troublesome symptoms. Quetiapine, as one of the most commonly prescribed antipsychotic medication worldwide, has been reported as an effective augmentation strategy to antidepressants. The right quetiapine dose and personalized quetiapine treatment are frequently challenging for clinicians. This study aimed to identify important influencing variables for quetiapine dose by maximizing the use of data from real world, and develop a predictive model of quetiapine dose through machine learning techniques to support selections for treatment regimens. METHODS: The study comprised 308 depressed patients who were medicated with quetiapine and hospitalized in the First Hospital of Hebei Medical University, from November 1, 2019, to August 31, 2022. To identify the important variables influencing the dose of quetiapine, a univariate analysis was applied. The prediction abilities of nine machine learning models (XGBoost, LightGBM, RF, GBDT, SVM, LR, ANN, DT) were compared. Algorithm with the optimal model performance was chosen to develop the prediction model. RESULTS: Four predictors were selected from 38 variables by the univariate analysis (p < 0.05), including quetiapine TDM value, age, mean corpuscular hemoglobin concentration, and total bile acid. Ultimately, the XGBoost algorithm was used to create a prediction model for quetiapine dose that had the greatest predictive performance (accuracy = 0.69) out of nine models. In the testing cohort (62 cases), a total of 43 cases were correctly predicted of the quetiapine dose regimen. In dose subgroup analysis, AUROC for patients with daily dose of 100 mg, 200 mg, 300 mg and 400 mg were 0.99, 0.75, 0.93 and 0.86, respectively. CONCLUSIONS: In this work, machine learning techniques are used for the first time to estimate the dose of quetiapine for patients with depression, which is valuable for the clinical drug recommendations.

Novel, high accuracy models for hepatocellular carcinoma prediction based on longitudinal data and cell-free DNA signatures.

BACKGROUND & AIMS: Current hepatocellular carcinoma (HCC) risk scores do not reflect changes in HCC risk resulting from liver disease progression/regression over time. We aimed to develop and validate two novel prediction models using multivariate longitudinal data, with or without cell-free DNA (cfDNA) signatures. METHODS: A total of 13,728 patients from two nationwide multicenter prospective observational cohorts, the majority of whom had chronic hepatitis B, were enrolled. aMAP score, as one of the most promising HCC prediction models, was evaluated for each patient. Low-pass whole-genome sequencing was used to derive multi-modal cfDNA fragmentomics features. A longitudinal discriminant analysis algorithm was used to model longitudinal profiles of patient biomarkers and estimate the risk of HCC development. RESULTS: We developed and externally validated two novel HCC prediction models with a greater accuracy, termed aMAP-2 and aMAP-2 Plus scores. The aMAP-2 score, calculated with longitudinal data on the aMAP score and alpha-fetoprotein values during an up to 8-year follow-up, performed superbly in the training and external validation cohorts (AUC 0.83-0.84). The aMAP-2 score showed further improvement and accurately divided aMAP-defined high-risk patients into two groups with 5-year cumulative HCC incidences of 23.4% and 4.1%, respectively (p = 0.0065). The aMAP-2 Plus score, which incorporates cfDNA signatures (nucleosome, fragment and motif scores), optimized the prediction of HCC development, especially for patients with cirrhosis (AUC 0.85-0.89). Importantly, the stepwise approach (aMAP -> aMAP-2 -> aMAP-2 Plus) stratified patients with cirrhosis into two groups, comprising 90% and 10% of the cohort, with an annual HCC incidence of 0.8% and 12.5%, respectively (p <0.0001). CONCLUSIONS: aMAP-2 and aMAP-2 Plus scores are highly accurate in predicting HCC. The stepwise application of aMAP scores provides an improved enrichment strategy, identifying patients at a high risk of HCC, which could effectively guide individualized HCC surveillance. IMPACT AND IMPLICATIONS: In this multicenter nationwide cohort study, we developed and externally validated two novel hepatocellular carcinoma (HCC) risk prediction models (called aMAP-2 and aMAP-2 Plus scores), using longitudinal discriminant analysis algorithm and longitudinal data (i.e., aMAP and alpha-fetoprotein) with or without the addition of cell-free DNA signatures, based on 13,728 patients from 61 centers across mainland China. Our findings demonstrated that the performance of aMAP-2 and aMAP-2 Plus scores was markedly better than the original aMAP score, and any other existing HCC risk scores across all subsets, especially for patients with cirrhosis. More importantly, the stepwise application of aMAP scores (aMAP -> aMAP-2 -> aMAP-2 Plus) provides an improved enrichment strategy, identifying patients at high risk of HCC, which could effectively guide individualized HCC surveillance.

Hourglass-Shaped Nanocages with Concaved Structures Based on Selective Self-Complementary Coordination Ligands and Tunable Hierarchical Self-Assembly.

Three-dimensional (3D) structures constructed via coordination-driven self-assemblies have recently garnered increasing attention due to the challenges in structural design and potential applications. In particular, developing new strategy for the convenient and precise self-assemblies of 3D supramolecular structures is of utmost interest. Introducing the concept of self-coordination ligands, herein the design and synthesis of two meta-modified terpyridyl ligands with selective self-complementary coordination moiety are reported and their capability to assemble into two hourglass-shaped nanocages SA and SB is demonstrated. Within these 3D structures, the meta-modified terpyridyl unit preferably coordinates with itself to serve as concave part. By changing the arm length of the ligands, hexamer (SA) and tetramer (SB) are obtained respectively. In-depth studies on the assembly mechanism of SA and SB indicate that the dimers could be formed first via self-complementary coordination and play crucial roles in controlling the final structures. Moreover, both SA and SB can go through hierarchical self-assemblies in solution as well as on solid-liquid interface, which are characterized by transmission electron microscope (TEM) and scanning tunneling microscopy (STM). It is further demonstrated that various higher-order assembly structures can be achieved by tuning the environmental conditions.

Transcriptomics and co-expression network analysis revealing candidate genes for the laccase activity of Trametes gibbosa.

BACKGROUND: Trametes gibbosa, which is a white-rot fungus of the Polyporaceae family found in the cold temperate zone, causes spongy white rot on wood. Laccase can oxidize benzene homologs and is one of the important oxidases for white rot fungi to degrade wood. However, the pathway of laccase synthesis in white rot fungi is unknown. RESULTS: The peak value of laccase activity reached 135.75 U/min/L on the 9th day. For laccase activity and RNA-seq data, gene expression was segmented into 24 modules. Turquoise and blue modules had greater associations with laccase activity (positively 0.94 and negatively -0.86, respectively). For biology function, these genes were concentrated on the cell cycle, citrate cycle, nicotinate, and nicotinamide metabolism, succinate dehydrogenase activity, flavin adenine dinucleotide binding, and oxidoreductase activity which are highly related to the laccase synthetic pathway. Among them, gene_8826 (MW199767), gene_7458 (MW199766), gene_61 (MW199765), gene_1741 (MH257605), and gene_11087 (MK805159) were identified as central genes. CONCLUSION: Laccase activity steadily increased in wood degradation. Laccase oxidation consumes oxygen to produce hydrogen ions and water during the degradation of wood. Some of the hydrogen ions produced can be combined by Flavin adenine dinucleotide (FAD) to form reduced Flavin dinucleotide (FADH2), which can be transmitted. Also, the fungus was starved of oxygen throughout fermentation, and the NADH and FADH2 are unable to transfer hydrogen under hypoxia, resulting in the inability of NAD and FAD to regenerate and inhibit the tricarboxylic acid cycle of cells. These key hub genes related to laccase activity play important roles in the molecular mechanisms of laccase synthesis for exploring industrial excellent strains.

Preoperative Frailty Assessment Predicts Postoperative Mortality, Delirium and Pneumonia in Elderly Lung Cancer Patients: A Retrospective Cohort Study.

BACKGROUND: The purpose of this study was to investigate the predictive value of the 5-factor modified frailty index (mFI-5) for postoperative mortality, delirium and pneumonia in patients over 65 years of age undergoing elective lung cancer surgery. METHODS: Data were collected from a single-center retrospective cohort study conducted in a general tertiary hospital from January 2017 to August 2019. In total, the study included 1372 elderly patients aged over 65 who underwent elective lung cancer surgery. They were divided into frail group (mFI-5, 2-5), prefrail group (mFI-5, 1) and robust group (mFI-5, 0) on the basis of mFI-5 classification. The primary outcome was postoperative 1-year all-cause mortality. Secondary outcomes were postoperative pneumonia and postoperative delirium. RESULTS: Frailty group had the highest incidence of postoperative delirium (frailty 31.2% versus prefrailty 1.6% versus robust 1.5%, p < 0.001), postoperative pneumonia (frailty 23.5% versus prefrailty 7.2% versus robust 7.7%, p < 0.001), and postoperative 1-year mortality (frailty 7.0% versus prefrailty 2.2% versus robust 1.9%. p < 0.001). Frail patients have significantly longer length of hospitalization than those in the robust group and prefrail patients (p < 0.001). Multivariate analysis showed a clear link between frailty and increased risk of postoperative delirium (aOR 2.775, 95% CI 1.776-5.417, p < 0.001), postoperative pneumonia (aOR 3.291, 95% CI 2.169-4.993, p < 0.001) and postoperative 1-year mortality (aOR 3.364, 95% CI, 1.516-7.464, p = 0.003). CONCLUSIONS: mFI-5 has potential clinical utility in predicting postoperative death, delirium and pneumonia incidence in elderly patients undergoing radical lung cancer surgery. Frailty screening of patients (mFI-5) may provide benefits in risk stratification, targeted intervention efforts, and assist physicians in clinical decision-making.

A machine learning model for predicting blood concentration of quetiapine in patients with schizophrenia and depression based on real-world data.

AIMS: This study aimed to establish a prediction model of quetiapine concentration in patients with schizophrenia and depression, based on real-world data via machine learning techniques to assist clinical regimen decisions. METHODS: A total of 650 cases of quetiapine therapeutic drug monitoring (TDM) data from 483 patients at the First Hospital of Hebei Medical University from 1 November 2019 to 31 August 2022 were included in the study. Univariate analysis and sequential forward selection (SFS) were implemented to screen the important variables influencing quetiapine TDM. After 10-fold cross validation, the algorithm with the optimal model performance was selected for predicting quetiapine TDM among nine models. SHapley Additive exPlanation was applied for model interpretation. RESULTS: Four variables (daily dose of quetiapine, type of mental illness, sex and CYP2D6 competitive substrates) were selected through univariate analysis (P < .05) and SFS to establish the models. The CatBoost algorithm with the best predictive ability (mean [SD] R2  = 0.63 ± 0.02, RMSE = 137.39 ± 10.56, MAE = 103.24 ± 7.23) was chosen for predicting quetiapine TDM among nine models. The mean (SD) accuracy of the predicted TDM within ±30% of the actual TDM was 49.46 ± 3.00%, and that of the recommended therapeutic range (200-750 ng mL-1 ) was 73.54 ± 8.3%. Compared with the PBPK model in a previous study, the CatBoost model shows slightly higher accuracy within ±100% of the actual value. CONCLUSIONS: This work is the first real-world study to predict the blood concentration of quetiapine in patients with schizophrenia and depression using artificial intelligent techniques, which is of significance and value for clinical medication guidance.

Construction of 1,3,5-Triazine-Based Prisms and Their Enhanced Solid-State Emissions.

In this study, two trigonal prisms based on the 1,3,5-triazine motif (SA and SB), distinguished by hydrophobic groups, were prepared by the self-assembly of tritopic terpyridine ligands and Zn(II) ions. SA and SB exhibited high luminescence efficiencies in the solid state, overcoming the fluorescence quenching of the 1,3,5-triazine group caused by π-π interactions. Notably, SA and SB exhibited different luminescence behaviors in the solution state and aggregation state. SB with 12 alkyl chains exhibited extremely weak fluorescence in a dilute solution, but its fluorescence intensity and photoluminescence quantum yield (PLQY) were significantly enhanced in the aggregated state (with the increase in the water fraction), especially in the solid state. Different from the gradually enhanced efficiency of SB, the PLQY of SA gradually decreased with the increase in aggregation but still maintained a high luminescence efficiency. These two complexes exhibited different modes to solve the fluorescence quenching of 1,3,5-triazine in the solid state. The hierarchical self-assembly of SB exhibited nanorods owing to the hydrophobic interactions of alky chains, while SA aggregated into spheres under the influence of π-π interactions.

Amine-Imine Nickel Catalysts with Pendant O-Donor Groups for Ethylene (Co)Polymerization.

The introduction of a secondary interaction is an efficient strategy to modulate transition-metal-catalyzed ethylene (co)polymerization. In this contribution, O-donor groups were suspended on amine-imine ligands to synthesize a series of nickel complexes. By adjusting the interaction between the nickel metal center and the O-donor group on the ligands, these nickel complexes exhibited high activities for ethylene polymerization (up to 3.48 × 106 gPE·molNi-1·h-1) with high molecular weight up to 5.59 × 105 g·mol-1 and produced good polyethylene elastomers (strain recovery (SR) = 69-81%). In addition, these nickel complexes can catalyze the copolymerization of ethylene with vinyl acetic acid, 6-chloro-1-hexene, 10-undecylenic, 10-undecenoic acid, and 10-undecylenic alcohol to prepare the functionalized polyolefins.

Science in China: 30 years on.

Three decades after introducing market reforms and opening up to the rest of the world, China has become a major economic power. As the country prepares to show the world its sporting might, its competitiveness in life sciences may still need a boost.

Unique and generic crossed metabolism in response to four sub-lethal environmental stresses in the oriental fruit fly, Bactrocera dorsalis Hendel.

Bactrocera dorsalis is a well-known invasive pest that causes considerable ecological and economic losses worldwild. Although it has a wide environmental tolerance, few studies have reported its mechanism of adaptation to multiple sub-lethal environmental stresses. In this study, 38, 41, 39 and 34 metabolites changed significantly in B. dorsalis under four sub-lethal stresses (heat, cold, desiccation and hypoxia), as found by the metabolomic method. Therein, lactic acid and pyruvic acid were induced, whereas metabolites in the tricarboxylic acid (TCA) cycle such as citric acid, α-ketoglutarate acid, malic acid and fumaric acid were reduced under at least one of the stresses. Enzyme activity and quantitative polymerase chain reaction (qPCR) analyses verified the repression of pyruvic acid proceeding into the TCA cycle. In addition, the levels of several cryoprotectants and membrane fatty acids in B. dorsalis were altered. The findings indicated that B. dorsalis has evolved shared metabolic pathways to adapt to heat, hypoxia and desiccation stresses, such as reducing energy consumption by activating the anaerobic glycolytic metabolism. Cryoprotectants and membrane fatty acids were produced to improve the efficiency of stress resistance. This study revealed the unique and generic crossed physiological mechanism of insects to adapt to various environmental stresses.

Effect of Hypoxia-Ischemia on the Expression of Iron-Related Proteins in Neonatal Rat Brains.

Hypoxic-ischemic white matter injury (WMI) pathogenesis in preterm infants is not well established, and iron-related proteins in the brain may play an important role in imbalanced iron metabolism. We aimed to investigate the iron-related protein changes in neonatal rats after hypoxia-ischemia (HI), clarify the role of iron-related proteins in hypoxic-ischemic WMI, and potentially provide a new target for the clinical treatment of hypoxic-ischemic WMI in preterm infants. We adopted a WMI animal model of bilateral common carotid artery electrocoagulation combined with hypoxia in neonatal 3-day-old Sprague-Dawley rats. We observed basic myelin protein (MBP) and iron-related protein expression in the brain (ferritin, transferrin receptor [TfR], and membrane iron transporter 1 [FPN1]) via Western blot and double immunofluorescence staining. The expression of MBP in the WMI group was significantly downregulated on postoperative days (PODs) 14, 28, and 56. Ferritin levels were significantly increased on PODs 3, 7, 14, and 28 and were most significant on POD 28, returning to the sham group level on POD 56. FPN1 levels were significantly increased on PODs 7, 28, and 56 and were still higher than those in the sham group on POD 56. TfR expression was significantly upregulated on PODs 1, 7, and 28 and returned to the sham group level on POD 56. Immunofluorescence staining showed that ferritin, TfR, and FPN1 were expressed in neurons, blood vessels, and oligodendrocytes in the cortex and corpus callosum on POD 28. Compared with the sham group, the immune-positive markers of three proteins in the WMI group were significantly increased. The expression of iron-related proteins in the brain (ferritin, FPN1, and TfR) showed spatiotemporal dynamic changes and may play an important role in hypoxic-ischemic WMI.

Functional analysis of 3 genes in xenobiotic detoxification pathway of Bursaphelenchus xylophilus against matrine.

Bursaphelenchus xylophilus is the causative agent of pine wilt disease. It has caused devastating damage to ecosystems worldwide, owing to the characteristic of being widely spread and uncontrollable. However, the current methods of control are mainly based on pesticides, which can cause irreversible damage to the ecosystem. Therefore, the search for new drug targets and the development of environmentally friendly nematicides is especially valuable. In this study, three key genes of the xenobiotic detoxification pathways were cloned from B. xylophilus, which were subsequently subjected to bioinformatic analysis. The bioassay experiment was carried out to determine the concentration of matrine required for further tests. Subsequently, enzyme activity detection and three gene expression pattern analysis were performed on matrine treated nematodes. Finally, RNA interference was conducted to verify the functions carried out by the three genes in combating matrine. The results indicated that cytochrome P450 and glutathione S-transferase of B. xylophilus were activated by matrine, which induced high expression of BxCYP33C4, BxGST1, and BxGST3. After RNA interference of three genes of B. xylophilus, the sensitivity of B. xylophilus to matrine was increased and the survival rate of nematodes was reduced to various degrees in comparison to the control group. Overall, the results fully demonstrated that BxCYP33C4, BxGST1, and BxGST3 are valuable drug targets for B. xylophilus. Furthermore, the results suggested that matrine has value for development and exploitation in the prevention and treatment of B. xylophilus.

Exploring the role of detoxification genes in the resistance of Bursaphelenchus xylophilus to different exogenous nematicidal substances using transcriptomic analyses.

Bursaphelenchus xylophilus (Pine wood nematode, PWN) has become a worldwide forest disease due to its rapid infection ability, high lethality and difficulty in control. The main means of countering B. xylophilus is currently chemical control, but nematicides can present problems such as environmental pollution and drug resistance. The development of novel environmentally-friendly nematicides has thus become a focus of recent research. In this study, BxUGT3 and BxUGT34, which might be related to detoxification, were investigated by comparing transcriptomic and WGCNA approaches. Three other genes with a similar expression pattern, BxUGT13, BxUGT14, and BxUGT16, were found by gene family analysis. Further bioassays and qPCR assays confirmed that these five genes showed significant changes in transcript levels upon exposure to α-pinene and carvone, demonstrating that they respond to exogenous nematicidal substances. Finally, RNAi and bioassays showed that B. xylophilus with silenced BxUGT16 had increased mortality in the face of α-pinene and carvone stress, suggesting that BxUGT16 plays an important role in detoxification. Taken together, this study used novel molecular research methods, explored the detoxification mechanism of B. xylophilus at a transcriptomic level, and revealed a molecular target for the development of novel biopesticides.

Design and synthesis of novel quinazolin-4(1H)-one derivatives as potent and selective inhibitors targeting AKR1B1.

Inhibition of aldose reductase (AKR1B1) is a promising option for the treatment of diabetic complications. However, most of the developed small molecule inhibitors lack selectivity or suffer from low bioactivity. To address this limitation, a novel series of quinazolin-4(1H)-one derivatives as potent and selective inhibitors of AKR1B1 were designed and synthesized. Aldose reductase inhibitory activities of the novel compounds were characterized by IC50 values ranging from 0.015 to 31.497 µM. Markedly enhanced selectivity of these derivatives was also recorded, which was further supported by docking studies. Of these inhibitors, compound 5g exhibited the highest inhibition activity with selectivity indices reaching 1190.8. The structure-activity relationship highlighted the importance of N1-acetic acid and N3-benzyl groups with electron-withdrawing substituents on the quinazolin-4(1H)-one scaffold for the construction of efficient and selective AKR1B1 inhibitors.

Tailored Supramolecular Cage for Efficient Bio-Labeling.

Fluorescent chemosensors are powerful imaging tools used in a broad range of biomedical fields. However, the application of fluorescent dyes in bioimaging still remains challenging, with small Stokes shifts, interfering signals, background noise, and self-quenching on current microscope configurations. In this work, we reported a supramolecular cage (CA) by coordination-driven self-assembly of benzothiadiazole derivatives and Eu(OTf)3. The CA exhibited high fluorescence with a quantum yield (QY) of 38.57%, good photoluminescence (PL) stability, and a large Stokes shift (153 nm). Furthermore, the CCK-8 assay against U87 glioblastoma cells verified the low cytotoxicity of CA. We revealed that the designed probes could be used as U87 cells targeting bioimaging.

Radiopaque fiducial markers as an aid to fabrication of an implant surgical guide for a patient with orthodontic brackets: A dental technique.

Designing implant surgical guides for patients undergoing orthodontics merely by merging data imaging and communications in medicine (DICOM) files generated from cone beam computed tomography (CBCT) images and standard tessellation language (STL) files generated from surface scanners is challenging because of the inaccuracy caused by metal artifacts. The present technique describes a straightforward and effective method of fabricating a surgical guide with the aid of fiducial markers made from cotton swabs and flowable resin. The implant surgical guide is designed by using a software program after the superimposition of digital scan and CBCT data. This chairside technique provides an accurate, convenient, and cost-effective option for the clinician.

Sigma-1 Receptor Activation Improves Oligodendrogenesis and Promotes White-Matter Integrity after Stroke in Mice with Diabetic Mellitus.

Diabetes mellitus (DM) is a major risk factor for stroke and exacerbates white-matter damage in focal cerebral ischemia. Our previous study showed that the sigma-1 receptor agonist PRE084 ameliorates bilateral common-carotid-artery occlusion-induced brain damage in mice. However, whether this protective effect can extend to white matter remains unclear. In this study, C57BL/6 mice were treated with high-fat diets (HFDs) combined with streptozotocin (STZ) injection to mimic type 2 diabetes mellitus (T2DM). Focal cerebral ischemia in T2DM mice was established via injection of the vasoconstrictor peptide endothelin-1 (ET-1) into the hippocampus. Three different treatment plans were used in this study. In one plan, 1 mg/kg of PRE084 (intraperitoneally) was administered for 7 d before ET-1 injection; the mice were sacrificed 24 h after ET-1 injection. In another plan, PRE084 treatment was initiated 24 h after ET-1 injection and lasted for 7 d. In the third plan, PRE084 treatment was initiated 24 h after ET-1 injection and lasted for 21 d. The Y-maze, novel object recognition, and passive avoidance tests were used to assess neurobehavioral outcomes. We found no cognitive dysfunction or white-matter damage 24 h after ET-1 injection. However, 7 and 21 d after ET-1 injection, the mice showed significant cognitive impairment and white-matter damage. Only PRE084 treatment for 21 d could improve this white-matter injury; increase axon and myelin density; decrease demyelination; and increase the expressions of myelin regulator 2'-3'-cyclic nucleotide 3'-phosphodiesterase (CNpase) and myelin oligodendrocyte protein (MOG) (which was expressed by mature oligodendrocytes), the number of nerve/glial-antigen 2 (NG2)-positive cells, and the expression of platelet-derived growth factor receptor-alpha (PDGFRα), all of which were expressed by oligodendrocyte progenitor cells in mice with diabetes and focal cerebral ischemia. These results indicate that maybe there was more severe white-matter damage in the focal cerebral ischemia of the diabetic mice than in the mice with normal blood glucose levels. Long-term sigma-1 receptor activation may promote oligodendrogenesis and white-matter functional recovery in patients with stroke and with diabetes.