Objective To identify the key influencing factors and role mechanisms of large-scale medical equip-ment allocation decision-making in public hospitals,and to provide a reference basis for optimizing resource alloca-tion strategies.Methods Through searching the literature related to large-scale medical equipment decision-making in public hospitals and combing the policies,the system of decision-making influencing factors was initially screened.The Delphi method and decision-making trial and evaluation laboratory method were used to obtain the key influencing factors of equipment allocation decision-making and to determine the interaction effects among the factors.Results A total of seven cause factors and nine effect factors were screened.Among them,cost-benefit analysis,equipment technical performance,and evaluation of similar equipment were the top three key drivers;leadership emphasis,equipment market price,and equipment supporting facilities were the top three key con-straints.Conclusion Priority be given to strengthening the management of driving factors,mainly by conducting a full-cycle assessment of cost-effectiveness,paying attention to the clinical value output of equipment technical performance,and monitoring regionally similar equipment.A dynamic response mechanism for constraints should be established,mainly to strengthen leadership decision-making,implement a centralized procurement price nego-tiation model and improve the pre-assessment system for ancillary facilities.

Objective:To observe and explore the therapeutic effect of ankle brain computer interface therapy based on motor imagination on the rehabilitation of lower limb motor function and balance ability in stroke patients with hemiplegia.Method:Total 40 patients with hemiplegia after stroke were randomly divided into an experimental group and a control group using a random number table method,with 20 people in each group.Both groups received con-ventional clinical medicine and conventional rehabilitation treatment.The control group was given additional an-kle stretching robot training,once a day,30min/times,for 2 weeks.The experimental group was given addition-al foot and ankle brain-computer interface treatment based on movement imagination,once a day,30min/time,for 2 weeks,before treatment.After 2 weeks of treatment(after treatment),the Hoggan Micro FET3 tester was used to measure the back flexion muscle strength and active joint range of motion(AROM);Clinical evaluation was conducted using the modified Ashworth muscle tension scale(MAS),Fugl-Meyer lower limb movement score(FMA-LE),Berg balance scale(BBS),functional walking scale(FAC),and 6-minute walk test(6MWT).Result:Three patients in the control group and three patients in the experimental group dropped off.After 2 weeks of treatments,significant improvements were observed on the dorsiflexion muscle strength,dorsiflexion AROM,FMA-LE,BBS,FAC,and 6MWT(P<0.05)in the two groups.The MAS of the experimental group improved significantly(P<0.05)compared with that before treatment.After treatment,there were significant differ-ences in AROM,FMA-LE,and BBS between the two groups(P<0.05).Conclusion:Motor imagery-foot and ankle brain-computer interface therapy can effectively improve lower limb motor function and balance in stroke hemiplegic patients.

Objective:To observe and explore the therapeutic effect of ankle brain computer interface therapy based on motor imagination on the rehabilitation of lower limb motor function and balance ability in stroke patients with hemiplegia.Method:Total 40 patients with hemiplegia after stroke were randomly divided into an experimental group and a control group using a random number table method,with 20 people in each group.Both groups received con-ventional clinical medicine and conventional rehabilitation treatment.The control group was given additional an-kle stretching robot training,once a day,30min/times,for 2 weeks.The experimental group was given addition-al foot and ankle brain-computer interface treatment based on movement imagination,once a day,30min/time,for 2 weeks,before treatment.After 2 weeks of treatment(after treatment),the Hoggan Micro FET3 tester was used to measure the back flexion muscle strength and active joint range of motion(AROM);Clinical evaluation was conducted using the modified Ashworth muscle tension scale(MAS),Fugl-Meyer lower limb movement score(FMA-LE),Berg balance scale(BBS),functional walking scale(FAC),and 6-minute walk test(6MWT).Result:Three patients in the control group and three patients in the experimental group dropped off.After 2 weeks of treatments,significant improvements were observed on the dorsiflexion muscle strength,dorsiflexion AROM,FMA-LE,BBS,FAC,and 6MWT(P<0.05)in the two groups.The MAS of the experimental group improved significantly(P<0.05)compared with that before treatment.After treatment,there were significant differ-ences in AROM,FMA-LE,and BBS between the two groups(P<0.05).Conclusion:Motor imagery-foot and ankle brain-computer interface therapy can effectively improve lower limb motor function and balance in stroke hemiplegic patients.

Objective To identify the key influencing factors and role mechanisms of large-scale medical equip-ment allocation decision-making in public hospitals,and to provide a reference basis for optimizing resource alloca-tion strategies.Methods Through searching the literature related to large-scale medical equipment decision-making in public hospitals and combing the policies,the system of decision-making influencing factors was initially screened.The Delphi method and decision-making trial and evaluation laboratory method were used to obtain the key influencing factors of equipment allocation decision-making and to determine the interaction effects among the factors.Results A total of seven cause factors and nine effect factors were screened.Among them,cost-benefit analysis,equipment technical performance,and evaluation of similar equipment were the top three key drivers;leadership emphasis,equipment market price,and equipment supporting facilities were the top three key con-straints.Conclusion Priority be given to strengthening the management of driving factors,mainly by conducting a full-cycle assessment of cost-effectiveness,paying attention to the clinical value output of equipment technical performance,and monitoring regionally similar equipment.A dynamic response mechanism for constraints should be established,mainly to strengthen leadership decision-making,implement a centralized procurement price nego-tiation model and improve the pre-assessment system for ancillary facilities.

Objective: To identify the functional connectivity characteristics of insula, sensory and social related brain regions in boys with autism spectrum disorder(ASD), to explore the central nervous basis of sensory abnormality affecting core symptoms in boys with ASD. Methods: Resting state functional magnetic resonance imaging (rs fMRI) data were collected from 34 boys with ASD and 29 typical development boys (TD group). Based on functional connectivity analysis, the sensory related brain regions, insula, and social related brain regions were taken as regions of interest to calculate the functional connectivity (FC) level between the regions of interest, the differences between the two groups were compared and the results were corrected by FDR. The Autism Diagnostic Observation Schedule (ADOS), Childhood Autism Rating Scale (CARS) and Autism Spectrum Quotient-Children s Version (AQ-Child) were used to assess the core phenotypes of boys with ASD. Results: Compared with the TD group, the levels of FC between tactile brain regions and insula, olfactory brain regions and insula, auditory brain regions and insula in boys with ASD group were significantly increased. The level of FC between the insula and bilateral amygdala，insula and the medial prefrontal cortex(mPFC) were significantly increased( P <0.05).Pearson correlation analysis showed that the level of FC between auditory brain region(BA42)and left insula in ASD group was negatively correlated with the scores of communication subscale of ADOS( r =-0.44)，social interaction subscale of ADOS( r =-0.43), communication & social interaction subscale of ADOS( r =-0.49),attention to details subscale of AQ-Child( r =-0.41). The level of FC between the right insula and right amygdala was positively correlated with the attention switch subscale of AQ-Child( r =0.38), the level of FC between right insula and mPFC was positively correlated with the scores of repetitive behavior subscale of ADOS( r =0.48), the attention switch subscale of AQ-Child( r =0.49), total scale subscale of AQ-Child( r =0.41), total scale of CARS( r =0.41)( P < 0.05 ). Conclusion The levels of FC between insula and sensory related, social related brain regions are abnormal in children with ASD, which have significant correlations with clinical symptoms. In depth studies can be conducted to explore underlying neutral mechanisms.

Objective: To explore the differences of sensory manifestations between ASD children and typical development children, and to clarify the characteristics of sensory abnormalities in ASD and their relationship with various clinical symptoms, so as to provide scientific basis for early identification and specific intervention. Methods: A total of 265 ASD children who received rehabilitation training in autism rehabilitation institutions in Heilongjiang Province were collected as the case group, and 223 typical development children in ordinary kindergartens and schools in Harbin were taken as the control group. Short Sensory Profile (SSP) was used to evaluate the difference of children s sensory perception level between the two groups, and Social Response Scale (SRS) and Autism Behavior Checklist (ABC) were used to evaluate the severity of symptoms including social disorder of autistic children. The correlation between SSP scores in ASD group and clinical scales was analyzed. Results: The comparison of SSP scores between the two groups found that the median scores of all sensory dimensions in ASD group (tactile=33, taste/smell=18, motion sensitivity=13, Low response/sensation seeking=28, auditory filtering=19, low strength=22, visual/auditory=20) were lower than those of the healthy control group( Z =-2.73,-4.36,-3.17,-5.09,-11.00,-10.45,-3.43, P <0.05). The abnormal rate of multisensory score in children in ASD group was 55.1%, and that in control group was 21.2%, with significant difference( χ 2=57.15, P <0.05). Correlation analysis showed that SSP score in ASD group was negatively correlated with all dimensions of SRS, nonverbal communication, and social function of ADI-R scale, ADOS communication and social interaction, and total scores of ABC and CARS( P < 0.05 ). Conclusion Children with ASD have atypical sensory experiences, especially in auditory filtering dimension, and the level of atypical sensation is related to the severity of clinical symptoms of autism. In the future clinical diagnosis, treatment and research, it is necessary to strengthen the ability to recognize the sensory symptoms of children with ASD, so as to realize the early diagnosis and intervention.

In 2011,the International Association for the Study of Lung Cancer(IASLC),American Thoracic Society(ATS)and European Respiratory Society(ERS)simultaneously defined micropapillary pattern(MPP)-based lung adenocarcinoma as an independent pathological type:micropapillary-predominant adenocarcinoma(MPA).Its histological and clinical specificities have attracted broad attention from researchers.Lung adenocarcinoma with a micropapillary pattern(MPPAC)often shows biological behaviors indicative of poor prognosis,including strong invasion,high metastasis rate and easy recurrence after surgical treatment.At present,the clinical diagnosis of MPPAC depends on postoperative pathological examination,but systematic studies on its pathological heterogeneity,molecular biological characteristics,clinical features and prognosis remains scarce.This review aims to focus on the research progress of the pathological and clinical features of MPPAC.

Objective: To explore the functional connectivity between the visual brain regions and whole brain in children with autism spectrum disorder (ASD) at resting state, and to further analyze the correlation with their clinical manifestations. Methods: The functional magnetic resonance imaging (fMRI) data of 34 boys with ASD enrolled from ASD designated rehabilitation institutions and 29 healthy boys enrolled from several kindergartens in Heilongjiang were collected. Based on the resting-state functional connectivity magnetic resonance imaging (rs-fc MRI) analysis, the BA17 of the primary visual brain region and the BA18/19 of the higher visual brain region were taken as the regions of interest (ROI) to calculate the functional connectivity level between the visual brain regions and whole brain, and the differences between the two groups were compared. Multiple developmental scales were used to evaluate the behavior of ASD children, and Pearson correlation analysis was used to explore the relationship between functional connection strength and autistic behavior. Results: The ASD group had decreased positive connectivity between BA17 and the right fusiform gyrus (FFG), and was negatively correlated with social interaction of ADI-R and the total scores of CARS (r=-0.41, -0.48, P<0.05); ASD group had decreased positive connectivity between BA17 and the left FFG, there was a negative correlation with social motivation of SRS (r=-0.43, P<0.05); ASD group had decreased positive connectivity between BA17 and the left posterior cingulate gyrus (PCG). Children with ASD had decreased positive connectivity between BA18/19 and left calcarine fissure and surrounding cortex (CAL), which was positively correlated with attention conversion of AQ, total scores of CARS (r=0.43, 0.40, P<0.05), and the children with ASD had deceased positive connectivity between BA18/19 and right precuneus (PCUN). Conclusion In resting state, the functional connectivity of primary and higher visual brain regions and whole brain of ASD children is different from that in healthy children, and there is a significant correlation between abnormal level and autistic behaviors.

Objective:To observe the effect of ankle stretching on ankle biomechanics, balance, walking ability and ability in the activities of daily living among stroke survivors.Methods:Eighteen hemiplegic stroke survivors were randomly divided into an experimental group ( n=9) and a control group ( n=9). In addition to routine medication and rehabilitation training, the experimental group received 20 minutes of ankle joint stretching daily while the control group underwent an additional twenty minutes of routine rehabilitation training. Before and after the treatment, both groups′ ankle joint stiffness (K), muscle strength, active range of motion (AROM) and passive range of motion (PROM) were evaluated. They were also assessed using the modified Ashworth scale (MAS), the Fugl-Meyer lower extremity assessment (FMA-LE), the Berg balance scale (BBS), the 6-minute walking test (6MWT) and the modified Barthel Index (MBI). Results:After two weeks of treatment significant improvement was observed in the AROM and muscle strength of both groups in dorsiflexion and plantarflexion. The average BBS and FMA-LE scores of both groups had also improved significantly. Significant improvement in the average PROM of plantarflexion and the K of dorsiflexion, as well as in average MBI score was observed only in the treatment group. After two weeks the treatment group′s average muscle strength in plantarflexion and dorsiflexion was significantly better than the control group′s.Conclusions:Stretching can reduce ankle stiffness, improve the range of motion, muscle strength, and ability of in the activities of daily living after a stroke.

The recovery of disorders of consciousness after brain injury is very difficult, music therapy is one of the important ways to promote the awakening. The effects of music therapy are various among individuals, the vegetative state and the minimally conscious state, and the pieces of music. The default mode network is one of the most important networks to maintain awareness, which many other networks participate in. The brain regions affected by music involve in many networks, including hearing, cognition, emotion, and so on.