Detection Method of Epileptic Seizures Using a Neural Network Model Based on Multimodal Dual-Stream Networks.

Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited recognizable features, and in order to increase the recognizable features in the input of the network, the differential features of the signals, the amplitude spectrum and the phase spectrum in the frequency domain are extracted to form a two-dimensional feature vector. In order to solve the problem of recognizing multimodal features, a neural network model based on a multimodal dual-stream network is proposed, which uses a mixture of one-dimensional convolution, two-dimensional convolution and LSTM neural networks to extract the spatial features of the EEG two-dimensional vectors and the temporal features of the signals, respectively, and combines the advantages of the two networks, using the hybrid neural network to extract both the temporal and spatial features of the signals at the same time. In addition, a channel attention module was used to focus the model on features related to seizures. Finally, multiple sets of experiments were conducted on the Bonn and New Delhi data sets, and the highest accuracy rates of 99.69% and 97.5% were obtained on the test set, respectively, verifying the superiority of the proposed model in the task of epileptic seizure detection.

Multi-classification method of arrhythmia based on multi-scale residual neural network and multi-channel data fusion.

Since ECG contains key characteristic information of arrhythmias, extracting this information is crucial for identifying arrhythmias. Based on this, in order to effectively extract ECG data features and realize automatic detection of arrhythmia, a multi-classification method of arrhythmia based on multi-scale residual neural network and multi-channel data fusion is proposed. First, the features of single-lead ECG signals are extracted and converted into two-dimensional images, and the feature data sets are labeled and divided according to different types of arrhythmias. The improved residual neural network is trained on the training set to obtain the classification model of the neural network. Finally, the classification model is applied to the automatic detection of arrhythmias during exercise. The accuracy of the classification model of this method is as high as 99.60%, and it has high accuracy and generalization ability. The automatic identification of arrhythmia also contributes to the research and development of future wearable devices.

Engineered geranyl diphosphate methyltransferase produces 2-methyl-dimethylallyl diphosphate as a noncanonical C6 unit for terpenoid biosynthesis.

Terpenoids constitute the largest class of natural products with complex structures, essential functions, and versatile applications. Creation of new building blocks beyond the conventional five-carbon (C5) units, dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate, expands significantly the chemical space of terpenoids. Structure-guided engineering of an S-adenosylmethionine-dependent geranyl diphosphate (GPP) C2-methyltransferase from Streptomyces coelicolor yielded variants converting DMAPP to a new C6 unit, 2-methyl-DMAPP. Mutation of the Gly residue at the position 202 resulted in a smaller substrate-binding pocket to fit DMAPP instead of its native substrate GPP. Replacement of Phe residue at the position 222 with a Tyr residue contributed to DMAPP binding via hydrogen bond. Furthermore, using Escherichia coli as the chassis, we demonstrated that 2-methyl-DMAPP was accepted as a start unit to generate noncanonical trans- and cis-prenyl diphosphates (C5n+1) and terpenoids. This work provides insights into substrate recognition of prenyl diphosphate methyltransferases, and strategies to diversify terpenoids by expanding the building block portfolio.

Depression signal correlation identification from different EEG channels based on CNN feature extraction.

Depression is a mental illness and can even lead to suicide if not be diagnosed and treated. Electroencephalograph (EEG) is used to diagnose depression and it is more complexity to extract the features from all the multimodal channel information . In order to simplify the diagnose process and detect clinical depression, the EEG channels with strong depression information should be identified firstly. Therefore, a depression signal correlation identification method based on convolutional neural network (CNN) is proposed. In the method, the labeled multi-channel EEG is used as data. The EEG signals of each channel are divided into neural network training data set and these data is trained by AlexNet network. Then the correlation classification of each channel for depression is identified based on the trained sample. Accuracy and loss functions are used to evaluate classification index.Conversely, the correlation is lower. An experiments is conducted and the results show that the correlation is not consistent. A few of channels are strongly correlated with depression, such as 13, 17, 28, 40, 46, 66 and 69. These EEG channels are selected to diagnose depression.

EEG diagnosis of depression based on multi-channel data fusion and clipping augmentation and convolutional neural network.

Depression is an undetectable mental disease. Most of the patients with depressive symptoms do not know that they are suffering from depression. Since the novel Coronavirus pandemic 2019, the number of patients with depression has increased rapidly. There are two kinds of traditional depression diagnosis. One is that professional psychiatrists make diagnosis results for patients, but it is not conducive to large-scale depression detection. Another is to use electroencephalography (EEG) to record neuronal activity. Then, the features of the EEG are extracted using manual or traditional machine learning methods to diagnose the state and type of depression. Although this method achieves good results, it does not fully utilize the multi-channel information of EEG. Aiming at this problem, an EEG diagnosis method for depression based on multi-channel data fusion cropping enhancement and convolutional neural network is proposed. First, the multi-channel EEG data are transformed into 2D images after multi-channel fusion (MCF) and multi-scale clipping (MSC) augmentation. Second, it is trained by a multi-channel convolutional neural network (MCNN). Finally, the trained model is loaded into the detection device to classify the input EEG signals. The experimental results show that the combination of MCF and MSC can make full use of the information contained in the single sensor records, and significantly improve the classification accuracy and clustering effect of depression diagnosis. The method has the advantages of low complexity and good robustness in signal processing and feature extraction, which is beneficial to the wide application of detection systems.

Gear Fault Diagnosis Method Based on Multi-Sensor Information Fusion and VGG.

The gearbox is an important component in the mechanical transmission system and plays a key role in aerospace, wind power and other fields. Gear failure is one of the main causes of gearbox failure, and therefore it is very important to accurately diagnose the type of gear failure under different operating conditions. Aiming at the problem that it is difficult to effectively identify the fault types of gears using traditional methods under complex and changeable working conditions, a fault diagnosis method based on multi-sensor information fusion and Visual Geometry Group (VGG) is proposed. First, the power spectral density is calculated with the raw frequency domain signal collected by multiple sensors before being transformed into a power spectral density energy map after information fusion. Second, the obtained energy map is combined with VGG to obtain the fault diagnosis model of the gear. Finally, two datasets are used to verify the effectiveness and generalization ability of the method. The experimental results show that the accuracy of the method can reach 100% at most on both datasets.

Exercise fatigue diagnosis method based on short-time Fourier transform and convolutional neural network.

Reasonable exercise is beneficial to human health. However, it is difficult for ordinary athletes to judge whether they are already in a state of fatigue that is not suitable for exercise. In this case, it is easy to cause physical damage or even life-threatening. Therefore, to health sports, protecting the human body in sports not be injured by unreasonable sports, this study proposes an exercise fatigue diagnosis method based on short-time Fourier transform (STFT) and convolutional neural network (CNN). The method analyzes and diagnoses the real-time electrocardiogram, and obtains whether the current exerciser has exercise fatigue according to the electrocardiogram. The algorithm first performs short-time Fourier transform on the electrocardiogram (ECG) signal to obtain the time spectrum of the signal, which is divided into training set and validation set. The training set is then fed into the convolutional neural network for learning, and the network parameters are adjusted. Finally, the trained convolutional neural network model is applied to the test set, and the recognition result of fatigue level is output. The validity and feasibility of the method are verified by the ECG experiment of exercise fatigue degree. The experimental recognition accuracy rate can reach 97.70%, which proves that the constructed sports fatigue diagnosis model has high diagnostic accuracy and is feasible for practical application.

The Recognition Method of Athlete Exercise Intensity Based on ECG and PCG.

Athletes usually arrange their training plans and determine their training intensity according to the coach's experience and simple physical indicators such as heart rate during exercise. However, the accuracy of this method is poor, and the training plan and exercise intensity arranged according to this method can easily cause physical damage, or the training cannot meet the actual needs. Therefore, in order to realize the reasonable arrangement and monitoring of athletes' training, a method of human exercise intensity recognition based on ECG (electrocardiogram) and PCG (Phonocardiogram) is proposed. First, the ECG and PCG signals are fused into a two-dimensional image, and the dataset is marked and divided according to the different motion intensities. Then, the training set is trained with a CNN (convolutional neural network) to obtain the prediction model of the neural network. Finally, the neural network model is used to identify the ECG and PCG signals to judge the exercise intensity of the athlete, so as to adjust the training plan according to the exercise intensity. The recognition accuracy of the model on the dataset can reach 95.68%. Compared with the use of heart rate to detect the physical state during exercise, ECG records the total potential changes in the process of depolarization and repolarization of the heart, and PCG records the waveform of the beating sound of the heart, which contains richer feature information. Combined with the CNN method, the athlete's exercise intensity prediction model constructed by extracting the features of the athlete's ECG and PCG signals realizes the real-time monitoring of the athlete's exercise intensity and has high accuracy and generalization ability.

Enabling Efficient Genetic Manipulations in a Rare Actinomycete Pseudonocardia alni Shahu.

Pseudonocardia species are emerging as important microorganisms of global concern with unique and increasingly significant ecological roles and represent a prominent source of bioactive natural products, but genetic engineering of these organisms for biotechnological applications is greatly hindered due to the limitation of efficient genetic manipulation tools. In this regard, we report here the establishment of an efficient genetic manipulation system for a newly isolated strain, Pseudonocardia alni Shahu, based on plasmid conjugal transfer from Escherichia coli to Pseudonocardia. Conjugants were yielded upon determining the optimal ratio between the donor and recipient cells, and designed genome modifications were efficiently accomplished, including exogenous gene integration based on an integrative plasmid and chromosomal stretch removal by homologous recombination using a suicidal non-replicating vector. Collectively, this work has made the P. alni Shahu accessible for genetic engineering, and provided an important reference for developing genetic manipulation methods in other rare actinomycetes.

Heat-sensitive moxibustion self-administration in patients in the community with primary hypertension: A protocol for a multi-center, pragmatic, non-randomized trial.

BACKGROUND: Although the efficacy of antihypertensive drugs has been well established for primary hypertension, their effectiveness is always limited by side effects and poor compliance. Heat-sensitive moxibustion is an innovative acupoint stimulation therapy that is promising as a community health care intervention for hypertension. AIMS: This study aims to evaluate the pragmatic effectiveness and safety of heat-sensitive moxibustion self-administration by patients in the community with primary hypertension. METHODS: This study will adopt a multi-center, pragmatic, nonrandomized design. Six hundred patients with primary hypertension will be recruited from 4 communities. Each patient will choose to either receive heat-sensitive moxibustion self-administration + original antihypertensive drugs or maintain their original antihypertensive drugs without heat-sensitive moxibustion for 1 year. EXPECTED OUTCOMES: The primary outcome will be changes in systolic and diastolic blood pressures and the percentage changes in the doses of antihypertensive drugs. The secondary outcomes will be changes in quality of life assessed by a validated patient-reported outcome scale and the levels of fasting blood glucose, glycated hemoglobin, total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, urinary albumin, and serum creatinine. The proportion of patients with poor compliance with the heat-sensitive moxibustion regimen will also be evaluated as a secondary outcome. The safety of heat-sensitive moxibustion will be considered by analyzing the incidence of all and serious adverse events and their correlation with heat-sensitive moxibustion. DISCUSSION: The findings of this study will provide pragmatic evidence for heat-sensitive moxibustion self-administration in patients in the community with primary hypertension and may also establish an ethical basis for further randomized controlled trials. TRIAL REGISTRATION: The protocol of this trial was registered in ClinicalTrials.gov at May 11, 2020 (No. NCT04381520).

Endogenous Type I CRISPR-Cas: From Foreign DNA Defense to Prokaryotic Engineering.

Establishment of production platforms through prokaryotic engineering in microbial organisms would be one of the most efficient means for chemicals, protein, and biofuels production. Despite the fact that CRISPR (clustered regularly interspaced short palindromic repeats)-based technologies have readily emerged as powerful and versatile tools for genetic manipulations, their applications are generally limited in prokaryotes, possibly owing to the large size and severe cytotoxicity of the heterogeneous Cas (CRISPR-associated) effector. Nevertheless, the rich natural occurrence of CRISPR-Cas systems in many bacteria and most archaea holds great potential for endogenous CRISPR-based prokaryotic engineering. The endogenous CRISPR-Cas systems, with type I systems that constitute the most abundant and diverse group, would be repurposed as genetic manipulation tools once they are identified and characterized as functional in their native hosts. This article reviews the major progress made in understanding the mechanisms of invading DNA immunity by type I CRISPR-Cas and summarizes the practical applications of endogenous type I CRISPR-based toolkits for prokaryotic engineering.

Characterization and repurposing of the endogenous Type I-F CRISPR-Cas system of Zymomonas mobilis for genome engineering.

Application of CRISPR-based technologies in non-model microorganisms is currently very limited. Here, we reported efficient genome engineering of an important industrial microorganism, Zymomonas mobilis, by repurposing the endogenous Type I-F CRISPR-Cas system upon its functional characterization. This toolkit included a series of genome engineering plasmids, each carrying an artificial self-targeting CRISPR and a donor DNA for the recovery of recombinants. Through this toolkit, various genome engineering purposes were efficiently achieved, including knockout of ZMO0038 (100% efficiency), cas2/3 (100%), and a genomic fragment of >10 kb (50%), replacement of cas2/3 with mCherry gene (100%), in situ nucleotide substitution (100%) and His-tagging of ZMO0038 (100%), and multiplex gene deletion (18.75%) upon optimal donor size determination. Additionally, the Type I-F system was further applied for CRISPRi upon Cas2/3 depletion, which has been demonstrated to successfully silence the chromosomally integrated mCherry gene with its fluorescence intensity reduced by up to 88%. Moreover, we demonstrated that genome engineering efficiency could be improved under a restriction-modification (R-M) deficient background, suggesting the perturbance of genome editing by other co-existing DNA targeting modules such as the R-M system. This study might shed light on exploiting and improving CRISPR-Cas systems in other microorganisms for genome editing and metabolic engineering practices.

Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach.

OBJECTIVES: Identifying stroke during a 9-1-1 call is critical to timely prehospital care. However, emergency medical dispatchers (EMDs) recognize stroke in less than half of 9-1-1 calls, potentially due to the words used by callers to communicate stroke signs and symptoms. We hypothesized that callers do not typically use words and phrases considered to be classical descriptors of stroke, such as focal neurologic deficits, but that a mixed-methods approach can identify words and phrases commonly used by 9-1-1 callers to describe acute stroke victims. METHODS: We performed a mixed-method, retrospective study of 9-1-1 call audio recordings for adult patients with confirmed stroke who were transported by ambulance in a large urban city. Content analysis, a qualitative methodology, and computational linguistics, a quantitative methodology, were used to identify key words and phrases used by 9-1-1 callers to describe acute stroke victims. Because a caller's level of emotional distress contributes to the communication during a 9-1-1 call, the Emotional Content and Cooperation Score was scored by a multidisciplinary team. RESULTS: A total of 110 9-1-1 calls, received between June and September 2013, were analyzed. EMDs recognized stroke in 48% of calls, and the emotional state of most callers (95%) was calm. In 77% of calls in which EMDs recognized stroke, callers specifically used the word "stroke"; however, the word "stroke" was used in only 38% of calls. Vague, non-specific words and phrases were used to describe stroke victims' symptoms in 55% of calls, and 45% of callers used distractor words and phrases suggestive of non-stroke emergencies. Focal neurologic symptoms were described in 39% of calls. Computational linguistics identified 9 key words that were more commonly used in calls where the EMD identified stroke. These words were concordant with terms identified through qualitative content analysis. CONCLUSIONS: Most 9-1-1 callers used vague, non-specific, or distractor words and phrases and infrequently provide classic stroke descriptions during 9-1-1 calls for stroke. Both qualitative and quantitative methodologies identified similar key words and phrases associated with accurate EMD stroke recognition. This study suggests that tools incorporating commonly used words and phrases could potentially improve EMD stroke recognition.

Assessing the dermal compatibility of a new female incontinence product line.

CONTEXT: We have developed a line of products designed to better meet the overall needs of women suffering from urinary incontinence. The products are more discrete and contain a unique odor neutralizing technology (ONT). OBJECTIVE: This paper describes the overall skin compatibility program for this product line in which the new products were compared to negative controls and/or commercially marketed reference products with an established history of safe use. MATERIALS AND METHODS: Test products consisted of several product forms (light pads/pantiliners, moderate pads, briefs and taped diapers) with ONT and having various degrees of protection. Studies were conducted using standard protocols for 4-day and 21-day cumulative irritation, the Human Repeat Insult Patch Test (HRIPT), and the Behind-the-Knee (BTK) test for mechanical and chemical irritation. In one 4-day irritation study and one HRIPT, test subjects consisted of individuals with self-assessed sensitive skin. In addition, one 4-day study was conducted using normal skin sites, and sites compromised by tape stripping. Nonirritant controls were physiologic saline and/or current, commercially marketed incontinence products. All responses were evaluated by visual scoring of erythema. In addition, in the BTK, transepidermal water loss (TEWL) and adverse sensory effects collected from panelists' daily diaries were also evaluated. RESULTS AND DISCUSSION: Two 4-day cumulative irritation studies and one 21-day study demonstrated that a wide range of product forms (liners, light and moderate pads, briefs and adult diapers) produced skin reactions similar to the nonirritant controls. The 4-day study conducted using sensitive skin subjects showed good skin compatibility, and the test products were comparable to the nonirritant controls. In the 4-day study with both normal and compromised skin sites, test products produced mean erythema scores similar to the nonirritant controls. Three HRIPT separate studies confirm that the products do not induce contact sensitization, including one study conducted on individuals with self-assessed sensitive skin. In the BTK, test and control products produced similar irritation, as assessed by erythema, TEWL and sensory effects. CONCLUSION: The results from the patch tests and mechanical irritation test demonstrate good skin compatibility of the new line of products with the unique ONT. In addition, the forms of the product (i.e. liner, pad or brief), were equally compatible with skin.

Kinetic study on bonding reaction of gelatin with CdS nanopaticles by UV-visible spectroscopy.

The chemical kinetics on gelatin-CdS direct conjugates has been systematically investigated as a function of different temperature and reactant concentration (i.e. Cd(2+), S(2-) and gelatin) by UV-visible spectroscopy, for the first time. The nonlinear fitting and the differential method were used to calculate the initial rate based on the absorbance-time data. A double logarithmic linear equation for calculating the rate constant (k) and the reaction order (n) was introduced. The reaction kinetic parameters (n, k, Ea, and Z) and activation thermodynamic parameters (ΔG(≠), ΔH(≠), and ΔS(≠)) were obtained from variable temperature kinetic studies. The overall rate equation allowing evaluation of conditions that provide required reaction rate could be expressed as: r = 1.11 × 10(8) exp(-4971/T)[Cd(2+)][gelatin](0.6)[S(2-)](0.6) (M/S) The calculated values of the reaction rate are well coincide with the experimental results. A suitable kinetic model is also proposed. This work will provide guidance for the rational design of gelatin-directed syntheses of metal sulfide materials, and help to understand the biological effects of nanoparticles at the molecular level.

Dermatological testing of an improved apertured film surface for feminine hygiene pads.

CONTEXT: Apertured polyethylene films (AF) have been used as a surface for sanitary pads for decades because they are compatible with the skin and keep the pad surface drier. A modified film (AF-plus) with improved fluid handling and a smoother, suppler texture has been developed. We hypothesized that these changes would improve both performance and skin compatibility. However, distinguishing the skin effects of materials that are inherently mild is a challenge. OBJECTIVES: (i) To compare the skin irritation potential of pads with AF-plus modified film relative to the standard AF film and (ii) to assess the potential for the AF-plus film to induce delayed contact hypersensitivity. MATERIALS AND METHODS: Pads bearing the AF-plus film were compared to pads with the standard AF film in a behind-the-knee (BTK) test, which assesses the combination of chemical irritation and frictional effects of materials applied to the popliteal fossa under a semi-occlusive bandage. Erythema on the skin surface was scored with the naked eye and subsurface tissue erythema was visualized and scored using cross-polarized illumination. Skin dryness was scored with the naked eye only. One-sided statistical evaluations were performed to test the hypothesis of AF-plus film superiority. The potential of the AF-plus film to induce delayed contact hypersensitivity was assessed by a human repeat insult patch test (HRIPT). RESULTS: Pads with the AF-plus surface were significantly milder to skin in the BTK test, producing lower levels of both surface and subsurface tissue erythema. Moreover, subjects with preexisting erythema on the skin surface at study start developed comparatively less erythema over the course of the study overall with the AF-plus pad compared to the AF pad. No significant difference in skin dryness was observed between product groups. The AF-plus pad showed no evidence of inducing delayed contact hypersensitivity. CONCLUSIONS: The AF-plus pad was superior to the AF pad in terms of skin mildness as discerned by objectively scored surface and subsurface tissue erythema. In subjects with preexisting erythema, the AF-plus pad appeared to contribute less to the further development of inflammation under the test conditions. Given the compositional similarities in the two films, the results could point to more limited contribution of the AF-plus film to skin friction, one of the factors simulated by the BTK test protocol.

Reversibility of cardiac abnormalities in morbidly obese adolescents.

OBJECTIVES: The purpose of this study was to evaluate changes in cardiac geometry, systolic and diastolic function before and after weight loss in morbidly obese adolescents. BACKGROUND: Cardiac abnormalities are present in morbidly obese adolescents; however, it is unclear if they are reversible with weight loss. METHODS: Data from 38 adolescents (13 to 19 years; 29 females, 9 males, 33 Caucasians, 5 African Americans) were evaluated before and after bariatric surgery. Left ventricular mass (LVM), left ventricular (LV) geometry, systolic and diastolic function were assessed by echocardiography. Mean follow up was 10 +/- 3 months. RESULTS: Weight and body mass index decreased post-operatively (mean weight loss 59 +/- 15 kg, pre-operative body mass index 60 +/- 9 kg/m(2) vs. follow-up 40 +/- 8 kg/m(2), p < 0.0001). Change in LVM index (54 +/- 13 g/m(2.7) to 42 +/- 10 g/m(2.7), p < 0.0001) correlated with weight loss (r = 0.41, p = 0.01). Prevalence of concentric left ventricular hypertrophy (LVH) improved from 28% at pre-operative to only 3% at follow up (p = 0.007), and normal LV geometry improved from 36% to 79% at follow up (p = 0.009). Diastolic function also improved (mitral E/Ea lateral 7.7 +/- 2.3 at pre-operative vs. 6.3 +/- 1.6 at post-operative, p = 0.003). In addition, rate-pressure product improved suggesting decreased cardiac workload (p < 0.001). CONCLUSIONS: Elevated LVM index, concentric LVH, altered diastolic function, and cardiac workload significantly improve following surgically induced weight loss in morbidly obese adolescents. Large weight loss due to bariatric surgery improves predictors of future cardiovascular morbidity in these young people.

[Clinical observation on moxibustion and acupuncture at Zusanli (ST 36) for treatment of refractory facial paralysis].

OBJECTIVE: To observe clinical therapeutic effect of moxibustion and acupuncture at Zusanli (ST 36) on refractory facial paralysis. METHODS: Sixty cases were randomly divided into a test group and a control group, 30 cases in each group. The control group were treated with acupuncture at Hegu (LI 4), Taichong (LR 3), Touwei (ST 8), etc. , and the test group with acupuncture at the same points as those in the control group plus moxibustion and acupuncture at Zusanli (ST 36) with a warm-heat sense transmitting into the depth of the point along the needle body for the patient. RESULTS: The total effective rate of 93.3% in the test group was significantly better than 76.7 in the control group (P < 0.05); in the test group, the total effective rate for the patients with needling sensation propagating along the channel was 100%, which was significantly superior to 80.00% in the patients with no needling sensation propagating along the channel (P < 0.05). CONCLUSION: Moxibustion and acupuncture at Zusanli (ST 36) activating sensation propagating along channel as main way has a better therapeutic effect on refractory facial paralysis.

Characterization of antibodies to CA 125 that bind preferentially to the cell-associated form of the antigen.

OBJECTIVE: Antibodies to CA 125 have been used to predict relapse of ovarian cancer, but have performed poorly as therapeutic agents. One rationale for this is antibody binding to circulating shed antigen. Our aim in this study was to develop antibodies to human CA 125 that have enhanced selectivity for the cell-associated form of the antigen. METHODS: Monoclonal antibodies were raised to a recombinant fragment of CA 125 that included sequence proximal to the putative membrane attachment site. Antibodies were characterized in terms of their binding site, affinity and selectivity for cell-associated CA 125. RESULTS: In assays using patient-derived CA 125, a subset of high-affinity (KD <5 nM) monoclonal antibodies demonstrated a 10- to greater than 200-fold increase in selectivity for cell-associated CA 125 when compared with controls. Based on mapping of the various monoclonal antibodies obtained, it was determined that shedding of CA 125 most likely occurs in the most C-terminal repeat domain. CONCLUSION: Results from competition analysis using patient-derived shed antigen predict that the antibodies described in this study may have significantly enhanced tumor-targeting properties when compared with existing antibodies to CA 125 in a tumor environment having high concentrations (>10,000 CA 125 units) of shed CA 125.

[Effect of vertebral manipulation therapy on vertebro-basilar artery blood flow in cervical spondylosis of vertebral artery type].

OBJECTIVE: To observe the effect of vertebral manipulation (VM) therapy on vertebro-basilar artery (VBA) blood flow in patients with cervical spondylosis of vertebral artery type (CS-VAT) by transcranial Doppler (TCD) ultrasonic examination. METHODS: One hundred and fifty patients with CS-VAT were randomized into the VM group (n = 100) and the acupuncture group (n = 50), and treated for ten times as one therapeutic course. Changes of the contraction peak, the end-diastolic and average blood flow velocity of VBA before and after treatment in the two groups were observed and compared by TCD. RESULTS: Vp, Vd, Vm of LVA, RVA and BA in the two groups after treatment were all lowered, showing significant difference, excepting Vp of VBA in the acupuncture group, when compared with before treatment (P< 0.05 or P <0.01). Comparison between the two groups after treatment showed significant difference in Vp and Vm of LVA, Vp, Vd and Vm of RVA, Vp and Vm of VBA respectively (P<0.05, P <0.01). CONCLUSION: VM therapy in treating patients with CS-VAT shows therapeutic effect superior to VA therapy, which could significantly improve VBA blood flow.