Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.4.1.14 (SPS)
 813 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We conducted a retrospective longitudinal self-controlled study of 124 adult patients treated with resective surgery for medically uncontrolled partial epilepsy from 1949 to 1988. Approximately 65% of the patients experienced > 95% reduction in seizure frequency, and 75% had worthwhile improvement of at least 75% seizure reduction. Significant reductions were noted in all major seizure types treatable with resective surgery; complex partial (CPS), simple partial (SPS), and secondarily generalized tonic-clonic seizures (GTC) (all p < 0.05). Tissue pathology and region of resection did not provide significant information with respect to seizure outcome. EEG in the first postoperative year was an important predictor of long-term seizure outcome (p = 0.03). One third of the temporal lobe resected patients had neurologic deficits as a consequence of the resection as compared with 14% of patients with frontal resections (p = 0.03). One third of the deficits among the temporal lobe resected patients were considerable, with possible social implications. Half of the patients with preoperative focal spike activity had a normal EEG postoperatively. One fifth of patients maintained their preoperative epileptic focus after the operation, and about one fifth displayed new foci. Approximately one fourth of the patients were free of medication for a median of 16 years postoperatively, and 60% of patients who were seizure-free were still receiving medication. There was no operative mortality, but the late mortality, as expected, was higher than that of the general population. Two male patients (1.6%) committed suicide.
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PMID:Surgical treatment for partial epilepsy among Norwegian adults. 802

Introduction. Suicide has become a serious worldwide epidemic. Early detection of individual suicide risk in population is important for reducing suicide rates. Traditional methods are ineffective in identifying suicide risk in time, suggesting a need for novel techniques. This paper proposes to detect suicide risk on social media using a Chinese suicide dictionary. Methods. To build the Chinese suicide dictionary, eight researchers were recruited to select initial words from 4,653 posts published on Sina Weibo (the largest social media service provider in China) and two Chinese sentiment dictionaries (HowNet and NTUSD). Then, another three researchers were recruited to filter out irrelevant words. Finally, remaining words were further expanded using a corpus-based method. After building the Chinese suicide dictionary, we tested its performance in identifying suicide risk on Weibo. First, we made a comparison of the performance in both detecting suicidal expression in Weibo posts and evaluating individual levels of suicide risk between the dictionary-based identifications and the expert ratings. Second, to differentiate between individuals with high and non-high scores on self-rating measure of suicide risk (Suicidal Possibility Scale, SPS), we built Support Vector Machines (SVM) models on the Chinese suicide dictionary and the Simplified Chinese Linguistic Inquiry and Word Count (SCLIWC) program, respectively. After that, we made a comparison of the classification performance between two types of SVM models. Results and Discussion. Dictionary-based identifications were significantly correlated with expert ratings in terms of both detecting suicidal expression (r = 0.507) and evaluating individual suicide risk (r = 0.455). For the differentiation between individuals with high and non-high scores on SPS, the Chinese suicide dictionary (t1: F 1 = 0.48; t2: F 1 = 0.56) produced a more accurate identification than SCLIWC (t1: F 1 = 0.41; t2: F 1 = 0.48) on different observation windows. Conclusions. This paper confirms that, using social media, it is possible to implement real-time monitoring individual suicide risk in population. Results of this study may be useful to improve Chinese suicide prevention programs and may be insightful for other countries.
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PMID:Creating a Chinese suicide dictionary for identifying suicide risk on social media. 2671 32