Lactation mastitis: Promising alternative indicators for early diagnosis

Although lactation mastitis (LM) has been extensively researched, the incidence rate of LM remains a salient clinical problem. To reduce this incidence rate and achieve a better prognosis, early and specific quantitative indicators are particularly important. It has been found that milk electrolyte concentrations (chloride, potassium, and sodium) and electrical conductivity (EC) significantly change in the early stages of LM in an animal model. Several studies have evaluated EC for the detection of subclinical mastitis in cows. EC, chloride, and sodium content of milk were more accurate for predicting infection status than were other variables. In the early stages of LM, lactic sodium, chloride, and EC increase, but potassium decreases. However, these indicators have not been reported in the diagnosis of LM in humans. This review summarizes the pathogenesis and the mechanism of LM in terms of milk electrolyte concentration and EC, and aim to provide new ideas for the detection of sub-clinical mastitis in humans.     

低频电刺激联合生物反馈治疗子宫切除术后盆底功能障碍的效果观察

目的 探讨低频电刺激联合生物反馈治疗(子宫全切或子宫次切)术后盆底功能障碍的临床效果。方法 选择2017年6月～2019年2月在我院诊断治疗的子宫全切或次全切术后盆底功能障碍的患者100例为研究对象,随机分为观察组与对照组,每组50例。对照组实施盆底肌功能训练,观察组实施低频电刺激治疗及生物反馈治疗。比较两组治疗前后PFDI-20评分、最大尿流率、平均尿流率、排尿时间、残余尿、盆底电生理功能。结果(1)治疗后,两组PFDI-20评分较治疗前低,差异有统计学意义(P0.05);观察组治疗后PFDI-20评分较对照组低,差异有统计学意义(P0.05)。(2)治疗后,两组最大尿流率、平均尿流率均显著提高,与治疗前比较差异有统计学意义(P0.05);两组排尿时间短于治疗前,残余尿量少于治疗前,差异有统计学意义(P0.05)。治疗后,观察组相较于对照组,排尿时间更短,残余尿量更少,差异有统计学意义(P0.05)。(3)治疗后,两组Ⅰ类肌纤维肌力、Ⅱ类肌纤维肌力均高于治疗前,差异有统计学意义(P0.05);观察组治疗后Ⅰ类肌纤维肌力、Ⅱ类肌纤维肌力优于对照组,差异有统计学意义(P0.05)。结论 低频电刺激联合生物反馈治疗子宫切除术后盆底功能障碍可显著改善盆底电生理功能,改善排尿情况,改善症状。     

Ultrasound-Assist Extrusion Methods for the Fabrication of Polymer Nanocomposites Based on Polypropylene/Multi-Wall Carbon Nanotubes

Isotactic polypropylenes (iPP) with different melt flow indexes (MFI) were used to fabricate nanocomposites (NCs) with 10 wt % loadings of multi-wall carbon nanotubes (MWCNTs) using ultrasound-assisted extrusion methods to determine their effect on the morphology, melt flow, and electrical properties of the NCs. Three different types of iPPs were used with MFIs of 2.5, 34 and 1200 g/10 min. Four different NC fabrication methods based on melt extrusion were used. In the first method melt extrusion fabrication without ultrasound assistance was used. In the second and third methods, an ultrasound probe attached to a hot chamber located at the exit of the die was used to subject the sample to fixed frequency and variable frequency, respectively. The fourth method is similar to the first method, with the difference being that the carbon nanotubes were treated in a fluidized air-bed with an ultrasound probe before being used in the fabrication of the NCs with no ultrasound assistance during extrusion. The samples were characterized by MFI, Optical microscopy (OM), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), electrical surface resistivity, and electric charge. MFI decreases in all cases with addition of MWCNTs with the largest decrease observed for samples with the highest MFI. The surface resistivity, which ranged from 10¹³ to 10⁵ Ω/sq, and electric charge, were observed to depend on the ultrasound-assisted fabrication method as well as on the melt flow index of the iPP. A relationship between agglomerate size and area ratio with electric charge was found. Several trends in the overall data were identified and are discussed in terms of MFI and the different fabrication methods.     

How structural and functional MRI can inform dual-site tACS parameters: A case study in a clinical population and its pragmatic implications

BackgroundAbnormalities in frontoparietal network (FPN) were observed in many neuropsychiatric diseases including substance use disorders. A growing number of studies are using dual-site-tACS with frontoparietal synchronization to engage this network. However, a computational pathway to inform and optimize parameter space for frontoparietal synchronization is still lacking. In this case study, in a group of participants with methamphetamine use disorders, we proposed a computational pathway to extract optimal electrode montage while accounting for stimulation intensity using structural and functional MRI.MethodsSixty methamphetamine users completed an fMRI drug cue-reactivity task. Four main steps were taken to define electrode montage and adjust stimulation intensity using 4x1 high-definition (HD) electrodes for a dual-site-tACS; (1) Frontal seed was defined based on the maximum electric fields (EF) predicted by simulation of HD montage over DLPFC (F3/F4 in EEG 10–10), (2) frontal seed-to-whole brain context-dependent correlation was calculated to determine connected regions to frontal seeds, (3) center of connected cluster in parietal cortex was selected as a location for placing the second set of HD electrodes to shape the informed montage, (4) individualized head models were used to determine optimal stimulation intensity considering underlying brain structure. The informed montage was compared to montages with large electrodes and classic frontoparietal HD montages (F3-P3/F4-P4) in terms of tACS-induced EF and ROI-to-ROI task-based/resting-state connectivity.ResultsCompared to the large electrodes, HD frontoparietal montages allow for a finer control of the spatial peak fields in the main nodes of the FPN at the cost of lower maximum EF (large-pad/HD: max EF[V/m] = 0.37/0.11, number of cortical sub-regions that EF exceeds 50% of the max = 77/13). For defining stimulation targets based on EF patterns, using group-level head models compared to a single standard head model results in comparable but significantly different seed locations (6.43 mm Euclidean distance between the locations of the frontal maximum EF in standard-space). As expected, significant task-based/resting-state connections were only found between frontal-parietal locations in the informed montage. Cue-induced craving score was correlated with frontoparietal connectivity only in the informed montage (r = ?0.24). Stimulation intensity in the informed montage, and not in the classic HD montage, needs 40% reduction in the parietal site to reduce the disparity in EF between stimulation sites.ConclusionThis study provides some empirical insights to montage and dose selection in dual-site-tACS using individual brain structures and functions and proposes a computational pathway to use head models and functional MRI to define (1) optimum electrode montage for targeting FPN in a context of interest (drug-cue-reactivity) and (2) proper transcranial stimulation intensity.     

伤口组织与电刺激调控的相关性研究*

慢性伤口迁延不愈。外源性电刺激提供促进慢性伤口愈合的电流，其独特优势是使电荷调控伤口，促进伤 口愈合，具有良好的应用前景，并成为目前组织学研究者和临床医生的研究热点之一。现介绍一些常见慢性伤口 的形态学和电生理特性，主要探讨目前电荷调控伤口愈合的形态学改变、可能作用机制及其影响因素。     

From the Cover: Spatiotemporal variations of seismicity before major earthquakes in the Japanese area and their relation with the epicentral locations

Using the Japan Meteorological Agency earthquake catalog, we investigate the seismicity variations before major earthquakes in the Japanese region. We apply natural time, the new time frame, for calculating the fluctuations, termed β, of a certain parameter of seismicity, termed κ₁. In an earlier study, we found that β calculated for the entire Japanese region showed a minimum a few months before the shallow major earthquakes (magnitude larger than 7.6) that occurred in the region during the period from 1 January 1984 to 11 March 2011. In this study, by dividing the Japanese region into small areas, we carry out the β calculation on them. It was found that some small areas show β minimum almost simultaneously with the large area and such small areas clustered within a few hundred kilometers from the actual epicenter of the related main shocks. These results suggest that the present approach may help estimation of the epicentral location of forthcoming major earthquakes.In this study, we investigate the evolution of seismicity shortly before main shocks in the Japanese region, N2546E125148, using Japan Meteorological Agency (JMA) earthquake catalog as in ref 1. For this, we adopted the new time frame called natural time since our previous works using this time frame made the lead time of prediction as short as a few days (see below). For a time series comprising N earthquakes (EQs), the natural time χ_k is defined as χ_k = k/N, where k means the k^th EQ with energy Q_k (Fig. 1). Thus, the raw data for our investigation, to be read from the earthquake catalog, are χ_k = k/N and pk=Qk/∑n=1NQn, where p_k is the normalized energy. In natural time, we are interested in the order and energy of events but not in the time intervals between events.Open in a separate windowFig. 1.EQ sequence in (A) conventional time and (B) natural time. In B, Q_k is given in units of the energy ε corresponding to a 3.5M_JMA EQ.We first calculate a parameter called κ₁, which is defined as follows (2, 3), from the catalog.κ1=∑k=1Npkχk2−(∑k=1Npkχk)2=〈χ2〉−〈χ〉2.[1]We start the calculation of κ₁ at the time of initiation of Seismic Electric Signals (SES), the transient changes of the electric field of Earth that have long been successfully used for short-term EQ prediction (4, 5). The area to suffer a main shock is estimated on the basis of the selectivity map (4, 5) of the station that recorded the corresponding SES. Thus, we now have an area in which we count the small EQs of magnitude greater than or equal to a certain magnitude threshold that occur after the initiation of the SES. We then form time series of seismic events in natural time for this area each time a small EQ occurs, in other words, when the number of the events increases by one. The κ₁ value for each time series is computed for the pairs (χ_k,p_k) by considering that χ_k is “rescaled” to χ_k = k/(N +1) together with rescaling pk=Qk/∑n=1N+1Qn upon the occurrence of any additional event in the area. The resulting number of thus computed κ₁ values is usually of the order 10² to 10³ depending, of course, on the magnitude threshold adopted for the events that occurred after the SES initiation until the main shock occurrence. When we followed this procedure, it was found empirically that the values of κ₁ converge to 0.07 a few days before main shocks. Thus, by using the date of convergence to 0.07 for prediction, the lead times, which were a few months to a few weeks or so by SES data alone, were made, although empirically, as short as a few days (6, 7). In fact, the prominent seismic swarm activity in 2000 in the Izu Island region, Japan, was preceded by a pronounced SES activity 2 mo before it, and the approach of κ₁ to 0.07 was found a few days before the swarm onset (8). However, when SES data are not available, which is usually the case, it is not possible to follow the above procedure. To cope with this difficulty, in the previous work (1), we investigated the time change of the fluctuation of the κ₁ values during a few preseismic months for each EQ (which we call target EQ) over the large area N2546E125148 (Fig. 2A) for the period from 1 January 1984 to 11 March 2011, the day of M9.0 Tohoku EQ. Setting a threshold M_JMA = 3.5 to assure data completeness of JMA catalog, we were left with 47,204 EQs in the concerned period of about 326 mo: ∼150 EQs per month. For calculating the β values, we chose 200 EQs before target EQs to cover the seismicity in almost one and a half months.Open in a separate windowFig. 2.(A) The 47,204 EQs with M_JMA ≥ 3.5 that occurred during the period of our study. (B) Contours of the number of EQs per month within R = 250 km. Solid diamonds show the epicenters of six shallow EQs investigated in this study. (C) Contours of the natural time window W used in each of the 12,476 areas of radius R = 250 km with offset 0.1° from one another that have at least eight EQs per month.To obtain the fluctuation β of κ₁, we need many values of κ₁ for each target EQ. For this purpose, we first took an excerpt comprised of W successive EQs just before a target EQ from the seismic catalog. The number W was chosen to cover a period of a few months. For this excerpt, we form its subexcerpts Sj={Qj+k−1}k=1,2,…,N of consecutive N = 6 EQs (since at least six EQs are needed (2) for obtaining reliable κ₁) of energy Q_j+k?1 and natural time χ_k = k/N each. Further, pk=Qj+k−1/∑k=1NQj+k−1, and by sliding S_j over the excerpt of W EQs, j=1,2,…,W−N+1 (= W − 5), we calculate κ₁ using Eq. 1 for each j. We repeat this calculation for N=7,8,…,W, thus obtaining an ensemble of [(W − 4)(W − 5)]/2 (= 1 + 2 +…+ W − 5) κ₁ values. Then, we compute the average μ(κ₁) and the SD σ(κ₁) of thus obtained ensemble of [(W − 4)(W − 5)]/2 κ₁ values. The variability β of κ₁ for this excerpt W is defined to be β ≡ σ(κ₁)/μ(κ₁) and is assigned to the (W + 1)^th EQ, i.e., the target EQ.The time evolution of the β value can be pursued by sliding the excerpt through the EQ catalog. Namely, through the same process as above, β values assigned to (W + 2)^th, (W + 3)^th, … EQs in the catalog can be obtained.We found in ref. 1 that the fluctuation β of κ₁ values exhibited minimum a few months before all of the six shallow EQs of magnitude larger than 7.6 that occurred in the study period. A minimum of β ≡ σ(κ₁)/μ(κ₁) means large average and/or small deviation of κ₁ values (e.g., see ref. 9).In the present work, we calculate the β values for small areas before the six large EQs, which showed β minima of the large area.     

Efficacy of an electric toothbrush on plaque control compared to two manual toothbrushes

Objectives: This study aimed to compare an electric toothbrush with two manual toothbrushes, in their relative efficacy to control plaque. Design: Randomised clinical trial. Setting: Kerman Dental School, Iran. Participants: Forty‐five volunteer dental students were randomly assigned to one of three groups. All subjects received a baseline plaque assessment using O’Leary plaque index, and then a prophylaxis to achieve the plaque index of zero. Subjects were trained to brush twice daily, with their assigned device and return after 1 week and then after 2 weeks for plaque assessment. Chi‐squared and ANOVA were mainly used. Main outcome measure: Plaque assessment using O’Leary plaque index. Results: Although Jordan toothbrush consistently resulted in lower plaque indices compared to both manual toothbrushes, those differences were not statistically significant, F(2, 42) = 2.45, P = 0.10. Plaque reduction from week 1 to week 2 was significant in Jordan Power group (60%, from 13.46 to 5.44, P = 0.010) and Panbehriz Classic group (53%, from 20.92 to 9.91, P = 0.007). Conclusion: The results of this study shows no evidence of statistically significant difference in respect to plaque control, between Jordan Power electric toothbrush and either of Oral‐B Advantage or Panbehriz Classic manual brushes in a group of dental students after 2 weeks.     

智能化微型肌监控仪的研制

目的:研制一种能自动检测皮肤阻抗、自动跟踪并调节刺激强度、操作简便、携带方便的智能化口颌面部肌监控仪。方法:以PIC16C57单片机为硬件核心,设计五种电路。用软件完成对电路的控制以避免复杂硬件设计之稳定性差、体积大等缺点。结果:新型肌监控仪以PIC16C57为CPU,配合自动平衡电路、数控强度电路、功放电路、阻抗测量电路、LED显示电路,能够产生特殊的刺激波形,并能检测人体阻抗、自动调节强度,体积微小、操作简便。结论:新型智能化微型肌监控仪具有自动跟踪、自动调节强度、操作简便、疗效可靠等优点,适合于口颌面部肌功能的刺激调节。