A novel immune-related lncRNA signature predicts the prognosis and immune landscape in ccRCC.

BACKGROUND: As one of the most common tumors, the pathogenesis and progression of clear cell renal cell carcinoma (ccRCC) in the immune microenvironment are still unknown. METHODS: The differentially expressed immune-related lncRNA (DEirlncRNA) was screened through co-expression analysis and the limma package of R, which based on the ccRCC project of the TCGA database. Then, we designed the risk model by irlncRNA pairs. In RCC patients, we have compared the area under the curve, calculated the Akaike Information Criterion (AIC) value of the 5-year receiver operating characteristic curve, determined the cut-off point, and established the optimal model for distinguishing the high-risk group from the low-risk group. We used the model for immune system assessment, immune point detection and drug sensitivity analysis after verifying the feasibility of the above model through clinical features. RESULTS: In our study, 1541 irlncRNAs were included. 739 irlncRNAs were identified as DEirlncRNAs to construct irlncRNA pairs. Then, 38 candidate DEirlncRNA pairs were included in the best risk assessment model through improved LASSO regression analysis. As a result, we found that in addition to age and gender, T stage, M stage, N stage, grade and clinical stage are significantly related to risk. Moreover, univariate and multivariate Cox regression analysis results reveals that in addition to gender, age, grade, clinical stage and risk score are independent prognostic factors. The results show that patients in the high-risk group are positively correlated with tumor infiltrating immune cells when the above model is applied to the immune system. But they are negatively correlated with endothelial cells, macrophages M2, mast cell activation, and neutrophils. In addition, the risk model was positively correlated with overexpressed genes (CTLA, LAG3 and SETD2, P<0.05). Finally, risk models can also play as an important role in predicting the sensitivity of targeted drugs. CONCLUSIONS: The new risk model may be a new method to predict the prognosis and immune status of ccRCC.

Effect of intravenous lidocaine on the ED50 of propofol induction dose in elderly patients undergoing painless gastroscopy: a prospective, randomized, double-blinded, controlled study.

BACKGROUND: Intravenous lidocaine could be a potential alternative adjuvant to propofol-based sedation for gastroscopy in elderly patients. This study aimed to evaluate the effect of intravenous lidocaine on the median effective dose (ED50) of propofol induction dose in elderly patients undergoing painless gastroscopy. METHODS: The study included 70 patients aged ≥ 60 years undergoing painless gastroscopy with 64 randomly assigned to either group L (2% lidocaine 1.5 mg/kg, n = 31) or group N (equal volume normal saline, n = 33). All patients received propofol induction following 0.1 µg/kg intravenous sufentanil. The Dixon "up-and-down" sequential method was used, with a 1.5 mg/kg initial induction dose of propofol followed by a 0.1 mg/kg sequential variable dose. The primary endpoint was the ED50 of the propofol induction dose. The total propofol dose, recovery time, adverse events, and local anesthetic intoxication reactions were also recorded. RESULTS: The ED50 of propofol induction dose was 0.670 (95% confidence interval [CI] 0.216-0.827) mg/kg in group L and 1.118 (95% CI 0.803-1.232) mg/kg in group N. There was a statistically significant difference between the two groups (p < 0.001). The incidence of hypotension and propofol injection pain were lower in group L than in group N (p < 0.05). Furthermore, the orientation recovery time in group L was shorter compared to group N (p < 0.05). None of the participants in group L observed local anesthetic intoxication reactions after receiving lidocaine. CONCLUSIONS: The administration of intravenous lidocaine to elderly patients undergoing painless gastroscopy resulted in a significant 40% reduction in the ED50 of propofol induction dose, which may be related to the decreased incidence of hypotension and injection pain, as well as the improved post-gastroscopy orientation recovery. TRIAL REGISTRATION: ChiCTR, ChiCTR2200065530. Registered on 08 November 2022.

Ratiometric SERS aptasensing for simultaneous quantitative detection of histamine and tyramine in fishes.

Herein, a SiO2@Ag NPs core/shell nanoparticles were synthesized to fabricate a surface-enhanced Raman spectroscopy (SERS) sensor for the simultaneous determination of histamine (HIS) and tyramine (TYR) based on specific aptamer recognition and ratiometric strategy. SiO2@Ag NPs with 4-thiosaminophenol (4-ATP) and Nile blue A (NBA) molecules were used as an internal standard (IS) and labeled with aptamers corresponding to HIS and TYR, respectively. Raman reporter molecules ROX and Cy5 labeled complementary DNA (cDNA) were then hybridized with aptamers to form rigid double-stranded DNA. After the HIS and TYR were captured by their aptamers, resulting in the dissociation of cDNA and separated from the SERS substrate. Therefore, the SERS signal intensity at 1503 cm-1 of ROX and 1358 cm-1 of Cy5 tagged on the terminal of cDNA decreased with the concentration of HIS and TYR increasing, while the SERS signal intensity at 1079 cm-1 of 4-APT and 592 cm-1 of NBA on the substrate remain stable. Thus, the concentrations of HIS and TYR can be determined by the I1503/I1079 and I1358/I592 values, respectively. This sensing strategy achieves a lower detection limit of 0.2 ng/mL for HIS and 0.05 ng/mL for TYR, respectively, demonstrating promising applications in sensitive detection of BAs in animal-derived foodstuff.

Added value of chest CT images to a personalized prognostic model in acute respiratory distress syndrome: a retrospective study.

Background: Acute respiratory distress syndrome (ARDS) is a critical disease in the intensive care unit (ICU) with high morbidity and mortality. The accuracy for predicting ARDS patients' outcome with mechanical ventilation is limited, and most based on clinical information. Methods: The patients diagnosed with ARDS between January 2014 and June 2019 were retrospectively recruited. Radiomics features were extracted from the upper, middle, and lower levels of the lung, and were further analyzed with the primary outcome (28-day mortality after ARDS onset). The univariate and multivariate logistic regression analyses were applied to figure out risk factors. Various predictive models were constructed and compared. Results: Of 366 ARDS patients recruited in this study, 276 (median age, 64 years [interquartile range, 54-75 years]; 208 male) survive on the Day 28. Among all factors, the APACHE II Score (OR 2.607, 95% CI 1.896-3.584, P < 0.001), the Radiomics_Score of the middle lung (OR 2.230, 95% CI 1.387-3.583, P = 0.01), the Radiomics_Score of the lower lung (OR 1.633, 95% CI 1.143-2.333, P = 0.01) were associated with the 28-day mortality. The clinical_radiomics predictive model (AUC 0.813, 95% CI 0.767-0.850) show the best performance compared with the clinical model (AUC 0.758, 95% CI 0.710-0.802), the radiomics model (AUC 0.692, 95% CI 0.641-0.739) and the various ventilator parameter-based models (highest AUC 0.773, 95% CI 0.726-0.815). Conclusions: The radiomics features of chest CT images have incremental values in predicting the 28-day mortality in ARDS patients with mechanical ventilation. Supplementary Information: The online version contains supplementary material available at 10.1007/s42058-023-00116-x.

Distinguishing multiple primary lung cancers from intrapulmonary metastasis using CT-based radiomics.

PURPOSE: To develop CT-based radiomics models that can efficiently distinguish between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). METHOD: This retrospective study included 127 patients with 254 lung tumors pathologically proved as MPLCs or IPMs between May 2009 and January 2020. Radiomics features of lung tumors were extracted from baseline CT scans. Particularly, we incorporated tumor-focused, refined radiomics by calculating relative radiomics differences from paired tumors of individual patients. We applied the L1-norm regularization and analysis of variance to select informative radiomics features for constructing radiomics model (RM) and refined radiomics model (RRM). The performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). The two radiomics models were compared with the clinical-CT model (CCM, including clinical and CT semantic features). We incorporated both radiomics features to construct fusion model1 (FM1). We also, build fusion model2 (FM2) by combing both radiomics, clinical and CT semantic features. The performance of the FM1 and FM2 were further compared with that of the RRM. RESULTS: On the validation set, the RM achieved an AUC of 0.857. The RRM demonstrated improved performance (validation set AUC, 0.870) than the RM, and showed significant differences compared with the CCM (validation set AUC, 0.782). Fusion models further led prediction performance (validation set AUC, FM1:0.885; FM2:0.889). There were no significant differences among the performance of the FM1, the FM2 and the RRM. CONCLUSIONS: The CT-based radiomics models presented good performance on the discrimination between MPLCs and IPMs, demonstrating the potential for early diagnosis and treatment guidance for MPLCs and IPMs.

Genome-Wide Association and Expression Analysis of the Lipoxygenase Gene Family in Passiflora edulis Revealing PeLOX4 Might Be Involved in Fruit Ripeness and Ester Formation.

Aroma is an important factor in fruit quality. Passiflora edulis (passion fruit) is popular among consumers because of its rich flavor and nutritional value. Esters are the main components of the volatile aroma of passion fruit. Lipoxygenase (LOX), as the first key enzyme upstream of esters, may play an important role in the formation of passion fruit aroma. In this study, a total of 12 passion fruit LOX (PeLOX) members were screened out based on the Passiflora edulis genome database, which were distributed unevenly on 6 chromosomes, all containing the highly conserved lipoxygenase domain and some containing the PLAT domain. The gene structure, evolutionary analysis and cis-acting elements of the family members were predicted in this study. Transcriptome analysis showed that 12 PeLOX genes had different degrees of response to different abiotic stresses (drought stress, salt stress, cold stress, and high temperature). PeLOX1, PeLOX2, PeLOX7, PeLOX11, and PeLOX12 responded significantly to various abiotic stresses, while PeLOX8 and PeLOX9 had little change in expression in all stresses. Quantitative real-time PCR (qRT-PCR) in six tissues revealed that the 12 PeLOX genes exhibited tissue expression specificity, and the relative expression of most genes were particularly high in the roots, stems, and fruits. Focusing on passion fruit ripening and ester synthesis, the transcriptomic analysis showed that with the increase in fruit development and fruit maturity, the expression levels of PeLOX1, PeLOX9, PeLOX11, and PeLOX12 showed downregulated expression, while PeLOX2 and PeLOX4 showed upregulated expression. In particular, the upregulation trend of PeLOX4 was the most obvious, and the qRT-PCR results were consistent with the transcriptome result. Pearson correlation analysis showed that with the development and ripening of fruit, the expression level of PeLOX4, LOX enzyme activity and total ester content all showed an increasing trend, in particular during the period when the peel was red and shrank (from T2 to T3 stage), the esters' contents increased by 37.4 times; the highest expression levels were all in the T3 period. The results indicated that PeLOX4 may be a candidate gene involved in fruit ripeness and the formation of volatile aroma compounds, with the increase in fruit ripening, the expression level of PeLOX4 increased and the LOX enzyme activity increased accordingly, thereby promoting the synthesis of volatile esters in fruit pulp. Our discovery lays the foundation for the functional study of LOX in passion fruit.

A multicenter retrospective study of transurethral prostate split for benign prostate hyperplasia.

Background: Transurethral split of the prostate (TUSP) is effective in treating benign prostatic hyperplasia (BPH). However, there is still a lack of research focusing on the optimal target population for TUSP. This study aimed to compare the efficacy of TUSP in patients with different prostate volumes or ages. Methods: The study was a multicenter retrospective study. The outcomes of TUSP in BPH patients with different prostate volumes or different ages were compared. A total of 439 patients were included in the study. Patients were divided into two groups according to prostate volume, with a cut-off value of 50 mL. Similarly, the cut-off value for the age groups was 70 years. Baseline patient characteristics and perioperative outcomes were recorded. Follow-up was performed at 1, 6, and 12 months after surgery. Results: The mean age of the patients was 73.4 years, and the mean prostate volume was 51.2 mL. At 12-month follow-up after TUSP treatment, the patients' International Prostate Symptom Scores (IPSS), quality of life (QoL) scores, and postvoid residual (PVR) volumes decreased significantly, while peak urinary flow rate (Qmax) increased significantly. Intraoperative hemoglobin (Hb) reduction was significantly lower in the small volume group than in the large volume group. The incidence of postoperative urinary urgency and transient incontinence was lower in the small volume group. IPSS score, PVR, and Qmax in the small volume group showed more remarkable changes at several time points compared to the preoperative period. Postoperative pain scores were higher in the small volume group than in the large volume group. There were no differences between the two groups in terms of long-term complications. The younger group showed greater variation in PVR and Qmax at some time points but less variation in QoL than the older group. Conclusions: TUSP is overall safe and effective in treating BPH. This study showed differences in the outcomes of TUSP in treating different prostate volumes or ages of BPH patients. The optimal surgical approach for BPH patients might be selected clinically based on a combination of prostate volume or patient age.

PEGylated Poly-HDACi: A Designer Polyprodrug from Optimized Drug Units.

We designed, synthesized, and characterized a tri-block copolymer. Its hydrophobic part, a chain of histone deacetylase inhibitor (HDACi) prodrug, was symmetrically flanked by two identical PEG blocks, whereas the built-in HDACi was a linear molecule, terminated with a thiol at one end, and a hydroxyl group at the other. Such a feature facilitated end-to-end linkage of prodrugs through alternatively aligned disulfides and carbonates. The disulfides served dual roles: redox sensors of smart nanomedicine, and warheads of masked HDACi drugs. This approach, carefully designed to benefit both control-release and efficacy, is conceptually novel for optimizing drug units in nanomedicine. Micelles from this designer polyprodrug released only PEG, CO2 and HDACi, and synergized with DOX against HCT116 cells, demonstrating its widespread potential in combination therapy. Our work highlights, for the first time, the unique advantage of thiol-based drug molecules in nanomedicine design.

Association of Maternal Body Mass Index With Risk of Infant Mortality: A Dose-Response Meta-Analysis.

Objective: This study presumed that a high or low body mass index (BMI) might increase the risk of infant mortality. Therefore, a meta-analysis was performed to systematically assess the association between maternal BMI and the risk of infant mortality. Methods: The electronic databases, including Pubmed, Embase database, and Cochrane Library, were systemically searched by two investigators from inception to November 26th, 2020, with no language restriction. In parallel, a dose-response was assessed. Results: Finally, 22 cohort studies involving 13,532,293 participants were included into this paper, which showed that compared with normal BMI, maternal overweight significantly increased the risks of infant mortality [risk ratio (RR), 1.16; 95% confidence interval (CI), 1.13-1.19], neonatal mortality (RR, 1.23; 95% CI, 1.08-1.39), early neonatal mortality (RR, 1.55; 95% CI, 1.26-1.92) and post-neonatal mortality (RR, 1.18; 95% CI, 1.07-1.29). Similarly, maternal obesity significantly increased the risk of infant mortality (RR, 1.55; 95% CI, 1.41-1.70), neonatal mortality (RR, 1.55; 95% CI, 1.28-1.67), early neonatal mortality (RR, 1.37; 95% CI, 1.13-1.67), and post-neonatal mortality (RR, 1.30; 95% CI, 1.03-1.65), whereas maternal underweight potentially decreased the risk of infant mortality (RR, 0.93; 95% CI, 0.88-0.98). In the dose-response analysis, the risk of infant mortality significantly increased when the maternal BMI was >25 kg/m2. Conclusions: Maternal overweight or obesity significantly increases the risks of infant mortality, neonatal mortality, early neonatal mortality, and post-neonatal mortality compared with normal BMI in a dose-dependent manner. Besides, maternal underweight will not increase the risk of infant mortality, neonatal mortality, early neonatal mortality, or postneonatal mortality; instead, it tends to decrease the risk of infant mortality. Early weight management may provide potential benefits to infants, and more large-scale prospective studies are needed to verify this finding in the future.

Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: A retrospective multicentre study.

PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e., Filter-Guided Pyramid NETwork (FGP-NET). MATERIALS AND METHODS: We developed and validated FGP-NET on a collection of 2106 pulmonary nodules on computed tomography images which combined screened and clinically detected nodules, and performed external test (n = 341). The area under the curves (AUCs) of FGP-NET were assessed. A comparison study with a group of 126 skilled radiologists was conducted. On top of FGP-NET, we built up our HONORS which was composed of two solutions. In the Human Free Solution, we used the high sensitivity operating point for screened nodules, but the high specificity operating point for clinically detected nodules. In the Human-Machine Coupling Solution, we used the Youden point. RESULTS: FGP-NET achieved AUCs of 0.969 and 0.847 for internal and external test. The AUCs of the subsets of the external test set ranged from 0.890 to 0.942. The average sensitivity and specificity of the 126 radiologists were 72.2 ±â€¯15.1 % and 71.7 ±â€¯15.5 %, respectively, while a higher sensitivity (93.3 %) but a relatively inferior specificity (64.0 %) were achieved by FGP-NET. HONORS-guided FGP-NET identified benign nodules with high sensitivity (sensitivity,95.5 %; specificity, 72.5 %) in the screened nodules, and identified malignant nodules with high specificity (sensitivity, 31.0 %; specificity, 97.5 %) in the clinically detected nodules. These nodules could be reliably diagnosed without any intervention from radiologists, via the Human Free Solution. The remaining ambiguous nodules were diagnosed with high performance, which however required manual confirmation by radiologists, via the Human-Machine Coupling Solution. CONCLUSIONS: FGP-NET performed comparably to skilled radiologists in terms of diagnosing pulmonary nodules. HONORS, due to its high performance, might reliably contribute a second opinion, aiding in optimizing the clinical workflow.

Design and Implementation of Matryoshka-type Neutron Spectrometer.

ABSTRACT: Aiming at portability and mobility, the design and implementation of a portable neutron spectrometer, namely the Matryoshka-type Neutron Spectrometer, was completed while considering the idea of a Bonner Sphere Spectrometer. The Matryoshka-type Neutron Spectrometer used a spherical 3He proportional counter as a thermal neutron detector. A number of cylindrical acrylic cups with diameters from 4 cm to 40 cm were made as containers for water as a moderator. The Monte Carlo method was adopted in order to obtain the energy response matrix of the Matryoshka-type Neutron Spectrometer. During the measurement, each acrylic cup contained water as a moderator, and the 3He proportional counter was set to the geometric center to perform neutron counting. With the energy response matrix obtained above, the neutron spectrum was resolved by a classical inversion algorithm. After the measurement, water was drained and the acrylic cups were placed one inside the other, like a Matryoshka doll. The design of a Matryoshka-type Neutron Spectrometer has reduced the mass and volume of the Bonner Sphere Spectrometer and was not difficult to carry around. Comparison tests acquiring background and Am-Be source neutron spectra between the Matryoshka-type Neutron Spectrometer and Bonner Sphere Spectrometer proved the effectiveness of the Matryoshka-type Neutron Spectrometer.

Discrimination between transient and persistent subsolid pulmonary nodules on baseline CT using deep transfer learning.

OBJECTIVES: To develop and validate a deep learning model to discriminate transient from persistent subsolid nodules (SSNs) on baseline CT. METHODS: A cohort of 1414 SSNs, consisting of 319 transient SSNs in 168 individuals and 1095 persistent SSNs in 816 individuals, were identified on chest CT. The cohort was assigned by examination date into a development set of 996 SSNs, a tuning set of 212 SSNs, and a validation set of 206 SSNs. Our model was built by transfer learning, which was transferred from a well-performed deep learning model for pulmonary nodule classification. The performance of the model was compared with that of two experienced radiologists. Each nodule was categorized by Lung CT Screening Reporting and Data System (Lung-RADS) to further evaluate the performance and the potential clinical benefit of the model. Two methods were employed to visualize the learned features. RESULTS: Our model achieved an AUC of 0.926 on the validation set with an accuracy of 0.859, a sensitivity of 0.863, and a specificity of 0.858, and outperformed the radiologists. The model performed the best among Lung-RADS 2 nodules and maintained well performance among Lung-RADS 4 nodules. Feature visualization demonstrated the model's effectiveness in extracting features from images. CONCLUSIONS: The transfer learning model presented good performance on the discrimination between transient and persistent SSNs. A reliable diagnosis on nodule persistence can be achieved at baseline CT; thus, an early diagnosis as well as better patient care is available. KEY POINTS: • Deep learning can be used for the discrimination between transient and persistent subsolid nodules. • A transfer learning model can achieve good performance when it is transferred from a model with a similar task. • With the assistance of deep learning model, a reliable diagnosis on nodule persistence can be achieved at baseline CT, which can bring a better patient care strategy.

Lipo-Dipeptide as an Emulsifier: Performance and Possible Mechanism.

A lipo-dipeptide (C13-lysine-arginine, C13-KR) was designed as a potential emulsifier with good emulsifying properties under acidic condition. Compared with two traditional emulsifiers (whey protein isolate and Tween 80), C13-KR emulsion had the minimum mean size but the highest zeta potential (around +100 mV). Moreover, C13-KR emulsion showed better stability against environmental stresses, such as high salt concentrations and high temperature. The C13-KR particles had the fastest move rate around 400 Hz when it attained an equilibrium state. Furthermore, C13-KR emulsifier could sharply reduce the interfacial tension and had the lowest tension value at the oil/water interface. The interfacial tension of C13-KR emulsifier was only 3.6 mN/m (0.5% w/v). In conclusion, the lipo-dipeptide C13-KR could be considered as an emulsifier to produce emulsion under acidic condition.

Real-Time Monitoring of Gross Beta Radioactivity in Tap Water and Committed Effective Dose.

To achieve real-time monitoring of gross beta radioactivity in drinking water, a scintillating fiber array system was developed. Using this system, the gross beta radioactivity in tap water at Tsinghua University campus in Beijing was monitored, and the same water samples were measured using the evaporation concentration method as a comparison experiment. Finally, the annual committed effective doses to children and adults who drank the tap water for a long time were estimated. The results showed that the gross beta radioactivity in tap water was 0.09 ± 0.03 Bq L using the scintillating fiber array system and 0.076 ± 0.009 Bq L using the evaporation concentration method. The annual committed effective dose values were less than the dose reference level of 0.1 mSv y, as suggested by the World Health Organization. The scintillating fiber array system can be used for measuring gross beta radioactivity in drinking water and protecting public health.

Gross beta determination in drinking water using scintillating fiber array detector.

A scintillating fiber array detector for measuring gross beta counting is developed to monitor the real-time radioactivity in drinking water. The detector, placed in a stainless-steel tank, consists of 1096 scintillating fibers, both sides of which are connected to a photomultiplier tube. The detector parameters, including working voltage, background counting rate and stability, are tested, and the detection efficiency is calibrated using standard potassium chloride solution. Water samples are measured with the detector and the results are compared with those by evaporation method. The results show consistency with those by evaporation method. The background counting rate of the detector is 38.131 ±â€¯0.005 cps, and the detection efficiency for ß particles is 0.37 ±â€¯0.01 cps/(Bq/l). The MDAC of this system can be less than 1.0 Bq/l for ß particles in 120 min without pre-concentration.

Analysis on Enrichment and Mass of Uranium Materials With Time-Correlated Measurement.

Effective determination for enrichment of the uranium materials in heavy shielding is technically difficult to solve. Various technical methods so far have been proposed to deal with this problem. With the time-correlated coincidence measurement method, 14 MeV neutrons and fission spectrum neutrons are chosen to interrogate the uranium samples with different masses and enrichments. The fission spectrum neutrons are obtained by slowing down the 14 MeV neutrons. Results have shown that a good linear relationship exists between masses of the uranium materials (≤10% enriched U) that possess the same enrichment. A linear relationship also exists between enrichments of the uranium materials that possess the same mass.

Stabilizing HDAC11 with SAHA to assay slow-binding benzamide inhibitors.

Among 18 human histone deacetylases (HDAC), HDAC11 is least studied. MS275, a benzamide HDAC inhibitor (HDACi), was stereotypically considered to selectively target Class I HDACs. We verified this slow-binding inhibitor also targeted HDAC11. In a traditional enzyme based assay, MS275 at low concentrations surprisingly behaved as an agonist. This was attributed to the poor stability of HDAC11 which lost 40% activity in 3h at 37°C. By adding 0.2µM SAHA, HDAC11 activity was stabilized during the 3-h assay period. Since 0.2µM SAHA inhibited 50% HDAC11 activity, the apparent IC50' of MS275 was adjusted to the true IC50=0.65µM. Finally, the new method demonstrated its superiority in one-dose-screening assays by decreasing false negative results. This work highlighted an optimized strategy to assay slow-binding inhibitors of unstable proteins with known fast-binding inhibitors. It should be especially useful in a hit-discovery stage to find moderate potent compounds.

Exploiting Kalman Filtering Non-linear Exponential Fitting to Promote the Energy Resolution of 137Cs and 60Co Gamma Ray Spectra.

For Cs and Co gamma ray spectra, gamma ray energy is proportional to the amplitude of the pulse signal, and energy resolution can be improved by pulse signal processing with mathematical algorithms. Influenced by system measurement noise and baseline fluctuation, the pulse amplitude is difficult to calculate accurately. A method that combines the Kalman filter baseline estimation with the non-linear exponential fitting has been used. By this method, the pulse signal is divided into two parts: one is the raising edge before the pulse peak, and another is after the pulse peak. The pulse amplitude equals the difference between the pulse starting height and the pulse peak height. The pulse starting height is obtained by Kalman filter baseline estimation on the rising edge of the pulse starting point. The pulse peak height is calculated by nonlinear exponential fitting on the falling edge of the pulse highest point. When the sampling rate is 100 MHz, the pulse signals obtained from a Cd(Zn)Te detector are analyzed by this method. Results have shown that the processed pulses have a more distinguishable amplitude distribution; energy resolution for the Cs spectrum is approximately 2.97% at 662 keV (~19.66 keV FWHM), and for the Co spectrum it is 2.61% at 1,332 keV (~34.76 keV FWHM).

A sub-milligram-synthesis protocol for in vitro screening of HDAC11 inhibitors.

This work demonstrated the high efficiency of a sub-milligram-synthesis based medicinal chemistry method. Totally 72 compounds, consisting a tri-substituted pyrrolidine core, were prepared. Around 0.1mg of each compound was solid-phase synthesized. Based on the additive property of UV absorptions of unconjugated chromophores of a molecule, these compounds were quantified by UV measurement. A hit, whose IC50 value was 1.2µM in HDAC11 inhibition assays, highlights the applicability of the approach reported here in future optimization works.

Comparison of Near Addition Value Prescription Methods for Myopic Children.

PURPOSE: To compare personalized near addition values for myopic children that induce a reasonable phoria (Ph) (meeting Sheard's criterion) and induce a null lag of accommodation at near and to evaluate changes in these metrics after lens adaptation. METHODS: Fifty-three myopic children participated in this study. Accommodative response, Ph, and fusional amplitudes (FAs) were measured at 33 cm through multiple addition lenses (0D, +1.00D, +1.50D, +2.00D, +2.50D, +3.00D). The adaptation effect on measured parameters was evaluated after 6 min of near work with each addition. The FA/Ph ratios were calculated for each addition and fitted using a rational function to obtain the optimal addition value satisfying Sheard's criterion (FA/Ph ≥ 2). Lag of accommodation change in association with addition value was assessed using linear regressions to obtain the addition values inducing a null lag. RESULTS: Lag of accommodation (r = -0.987, p < 0.001) and Ph (r = -0.999, p < 0.001) decreased linearly with addition value. The 6-min adaptation induced a small but significant increase in accommodative lag and an exophoric shift (p < 0.05). Three FA/Ph patterns with respect to addition lenses were observed based on the near Ph: orthophoria/exophoria, low esophoria, and large esophoria. Addition values based on Sheard's criterion (mean ± SD, +2.16 ± 0.79D) were significantly lower than those based on null lag (+2.83 ± 0.44D, t = 19.86, p < 0.001). The FA/Ph ratio was less than 2.0 in 75.5% of subjects with additions determined through null accommodative lag. Additions determined through FA/Ph ≥ 2 induced a lag of accommodation of 0.38 ± 0.42D. CONCLUSIONS: Personalized near addition values using Sheard's criterion were lower than those obtained through null lag of accommodation. These values should allow a better binocular balance especially for exophoric children.