A Comparison between Teaching Methods in Secondary School Biology

The advent of cheaper SLR digital cameras and associated software has allowed the rapid creation of digital images. We explain three simple techniques that allow the generation of micrographs. A further technique is described that allows the production of an image from a full section of the microscope slide. Class sets of micrographs greatly enhance any discussion before or after the practical session.     

Cone–shell Raman spectroscopy (CSRS) for depth‐sensitive measurements in layered tissue

We report the development of a depth‐sensitive Raman spectroscopy system using the configuration of cone–shell excitation and cone detection. The system uses a 785 nm diode laser and three identical axicons for Raman excitation of the target sample in the form of a hollow conic section. The Raman scattered light from the sample, passed through the same (but solid) conic section, is collected for detection. Apart from its ability of probing larger depths (? few mm), an important attraction of the system is that the probing depths can be varied by simply varying the separation between axicons in the excitation arm. Furthermore, no adjustment is required in the sample arm, which is a significant advantage for noncontact, depth‐sensitive measurement. Evaluation of the performance of the developed setup on nonbiological phantom and biological tissue sample demonstrated its ability to recover Raman spectra of layers located at depths of ?2–3 mm beneath the surface.

     

A comparative assessment of support vector regression,artificial neural networks,and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

Soil organic carbon (SOC) is a key indicator of ecosystem health, with a great potential to affect climate change. This study aimed to develop, evaluate, and compare the performance of support vector regression (SVR), artificial neural network (ANN), and random forest (RF) models in predicting and mapping SOC stocks in the Eastern Mau Forest Reserve, Kenya. Auxiliary data, including soil sampling, climatic, topographic, and remotely-sensed data were used for model calibration. The calibrated models were applied to create prediction maps of SOC stocks that were validated using independent testing data. The results showed that the models overestimated SOC stocks. Random forest model with a mean error (ME) of −6.5 Mg C ha⁻¹ had the highest tendency for overestimation, while SVR model with an ME of −4.4 Mg C ha⁻¹ had the lowest tendency. Support vector regression model also had the lowest root mean squared error (RMSE) and the highest R² values (14.9 Mg C ha⁻¹ and 0.6, respectively); hence, it was the best method to predict SOC stocks. Artificial neural network predictions followed closely with RMSE, ME, and R² values of 15.5, −4.7, and 0.6, respectively. The three prediction maps broadly depicted similar spatial patterns of SOC stocks, with an increasing gradient of SOC stocks from east to west. The highest stocks were on the forest-dominated western and north-western parts, while the lowest stocks were on the cropland-dominated eastern part. The most important variable for explaining the observed spatial patterns of SOC stocks was total nitrogen concentration. Based on the close performance of SVR and ANN models, we proposed that both models should be calibrated, and then the best result applied for spatial prediction of target soil properties in other contexts.     

The impact of PSA and digital rectal examination on the risk of prostate cancer specific mortality in men with a PSA level <2.5 ng/ml

IntroductionIt is unknown whether a normal range, diagnostic serum prostate specific antigen (PSA) level's influence on prostate cancer specific mortality (PCSM) is dependent upon digital rectal examination (DRE) findings.MethodsBetween 2004 and 2007, 9081 men diagnosed with non-palpable (T1c, N = 1710) or palpable (T2–T4, N = 7371) and non-metastatic prostate cancer (PC) were identified from surveillance, epidemiology, and end results data, selected based on pre-treatment PSA < 2.5 ng/ml. A multivariable competing risks regression model evaluated whether DRE findings interacted with PSA level in predicting risk of PCSM.ResultsAfter median follow-up of 2.83 years, 118 of 548 deaths (21.5%) were due to PC. Increasing diagnostic PSA was associated with increased risk of PCSM (AHR = 3.52; 95% CI: 1.25–9.89; P = .017) in men with T1c, Gleason score 7–10 PC, but decreased PCSM risk (AHR = 0.66; 95% CI: 0.52–0.83; P < .001) for men with T2–T4 PC and any Gleason score.DiscussionFor men with diagnostic PSA level <2.5 ng/ml and palpable PC, risk of early PCSM increases by 34% for a 1 point decrease in PSA from 2. This suggests the existence of clinically detectable, low PSA secreting disease with an elevated risk of early PCSM, highlighting the importance of the DRE in men with PC and normal range, diagnostic PSA.     

冠状动脉CT造影对冠心病的临床诊断价值研究

目的：探讨研究冠状动脉CT造影检查对冠心病的临床诊断价值。方法：收集我院2012年1月至2013年10月共计70例临床怀疑为冠心病的患者,对这些患者分别进行冠状动脉CT造影检查和数字减影冠状动脉造影（DSA）检查,记录这两项检查所得结果及数据,以检查数据为基础对冠状动脉CT造影和数字减影冠状动脉造影检查的临床实验效果进行对比研究。结果：70例病人均可顺利完成以上两种检查,按照数字减影冠状动脉造影检查的标准,冠状动脉CT造影的敏感度为92.2%,特异度为97.4%、阳性预测率为90.5%、阴性预测率98%。结论：相对于数字减影冠状动脉造影检查,冠状动脉CT造影检查是一种更加安全、可靠、无创且更具临床指导意义的检测技术,因此可以推荐作为冠心病诊断的首选方法。     

大黄联合抗生素治疗脑出血合并肺部感染的临床疗效观察

目的：观察大黄联合抗生素治疗脑出血后肺部感染的临床疗效。方法：96例急性高血压脑出血血肿清除术后并发肺部感染患者随机分为治疗组（56例）和对照组（40例）。对照组应用抗生素治疗,治疗组在抗生素治疗的基础上加用大黄6g,以温开水100mL调匀后经胃管鼻饲,每日2次,共治疗7天。治疗结束后比较和评价两组的治疗效果效果。结果：治疗组患者肺哆音消失的时间、炎症消散的时间和平均治愈天数分别为3．52±1．81、10．32±3．25、10．73±3．26天,较对照组（分别为10．86±3．43、13．51±2．66、14．73±3．11）均显著缩短,差异有显著统计学意义（P〈0．01）。治疗组和对照组治疗总有效率分别为94．64％和85％,差异有统计学意义（P〈0．05）。两组不良反应的发生率比较无统计学差异（P〉0．05）。结论：大黄联合抗生素治疗脑出血术后合并肺部感染,可缩短治疗时间,提高疗效,且无严重不良反应。     

EVIDENCE FOR MECHANOSENSITIVE TRANSMEMBRANE ION CHANNELS OF SMALL CONDUCTANCE IN MAGNETOTACTIC BACTERIA

To determine whether or not mechanosensitive (MS) ion channels are present in the magnetotactic bacterium Magnetospirillum magnetotacticum, techniques for spheroplast preparation in Escherichia coli were adapted for this bacterium. This resulted in the formation of 2–3-μm spheroplasts, which were used for patch clamp analysis. Ion channel activity in M. magnetotacticum was compared with that of the MS of small conductance (MscS) in E. coli. This comparison reveals the presence of MscS-like channels in M. magnetotacticum and, as this bacterium produces intracellular magnetite (Fe₃O₄) particles similar to those found in the human brain, provides a model for investigation of the effects of magnetic fields on MS ion channels in magnetite-bearing cells.     

越鞠方加减联合益生菌对幽门螺杆菌阳性慢性胃炎患者的疗效

目的探讨越鞠方加减联合益生菌对幽门螺杆菌(H.pylori)阳性慢性胃炎患者胃肠功能及血清血管活性肠肽(VIP)、生长激素释放肽(Ghrelin)的影响。方法选取2017年6月至2019年6月我院收治的128例H.pylori阳性慢性胃炎患者为研究对象,采用随机数字表法分为研究组和对照组,各64例。两组患者均给予标准四联疗法治疗,在此基础上,对照组患者加用益生菌进行治疗,研究组患者采用越鞠方加减联合益生菌进行治疗。比较两组患者中医治疗效果、H.pylori根除率、康复情况(胃肠功能恢复正常时间、症状改善时间、住院时间)、不良反应发生率、治疗前后血清VIP和Ghrelin水平及转化生长因子-β1(TGF-β1)、IL-6、IL-32水平。治疗后随访6个月,对比两组患者治疗后3个月和6个月的复发率。结果研究组患者治疗总有效率(93.75%)高于对照组(79.69%)。研究组患者胃肠功能恢复正常时间、症状改善时间及住院时间均短于对照组,H.pylori根除率(96.88%)高于对照组(81.25%),差异均有统计学意义(均P0.05)。研究组患者治疗后血清VIP水平低于对照组,Ghrelin水平高于对照组,同时血清TGF-β1、IL-6、IL-32水平低于对照组(均P0.05)。研究组患者不良反应总发生率(6.25%)与对照组(10.94%)比较差异无统计学意义(P0.05)。研究组患者治疗后3个月和6个月复发率与对照组比较差异无统计学意义(均P0.05)。结论采用越鞠方加减联合益生菌能显著提高H.pylori阳性慢性胃炎患者H.pylori根除率,进一步下调患者VIP水平,促进Ghrelin合成,抑制炎症反应,促进患者康复,安全性较高。     

乳腺三维断层技术结合乳腺超声对致密型乳腺病变的诊断价值

摘要 目的：探讨乳腺三维断层技术（DBT）结合乳腺超声(BUS)对致密型乳腺病变的诊断价值。方法：回顾分析2018年6月至2019年4月在我院就诊且有完整病理结果的149例致密型乳腺病变患者的影像资料,对比DBT、BUS两种检查方法的检出率;以病理结果为金标准,分析DBT、BUS、DBT联合BUS三种检查模式的诊断效能。结果：BUS对良性病变的检出率（97.87%）高于DBT（89.36%）,差异有统计学意义（x²=5.697,P＜0.05）;DBT与BUS对恶性病变的检出率分别为98.44%、95.31%,差异无统计学意义（x²=1.032,P>0.05）。DBT诊断致密型乳腺病变的敏感度为90.61%、特异度为93.55％、准确率为91.77％,BUS诊断致密型乳腺病变的敏感度为78.13%、特异度为89.36%、准确率为84.81%,DBT联合BUS诊断致密型乳腺病变的敏感度为95.31%、特异度为95.74%、准确率为95.57%。DBT联合BUS诊断致密型乳腺恶性病变的受试者工作特征曲线（ROC）的曲线下面积（AUC）为0.977,稍高于DBT的AUC（0.951）,明显高于BUS的AUC（0.885）。结论：BUS对良性病变的检出率显著高于DBT,DBT对致密型乳腺病变的诊断效能高于BUS,二者结合能提高病变的检出率与诊断效能。     

Identification and counting of fish targets using adaptive resolution imaging sonar

Fish are a critical component of marine biology; therefore, the accurate identification and counting of fish are essential for the objective monitoring and assessment of marine biological resources. High-frequency adaptive resolution imaging sonar (ARIS) is widely used for underwater object detection and imaging, and it quickly obtains close-up video of free-swimming fish in high-turbidity water environments. Nonetheless, processing the massive data output using imaging sonars remains a major challenge. Here, the authors developed an automatic image-processing programme that fuses K-nearest neighbour background subtraction with DeepSort target tracking to automatically track and count fish. The automatic programme was evaluated using four test data sets with different target sizes and observation ranges and differently deployed sonars. According to the results, the approach successfully counted free-swimming fish targets with an accuracy index of 73% and a completeness index of 70%. Under appropriate conditions, this approach could replace time-consuming semi-automatic approaches and improve the efficiency of imaging sonar data processing, while providing technical support for future real-time data processing.