Feasibility, safety, and efficacy of task-oriented mirrored robotic training on upper-limb functions and activities of daily living in subacute poststroke patients: a pilot study.

BACKGROUND: Robotic training with high repetitions facilitates upper-limb movements but provides fewer benefits for activities of daily living. Integrating activities of daily living training tasks and mirror therapy into a robot may enhance the functional gains of robotic training. AIM: The aim of this study was to investigate the feasibility, safety, and efficacy of the task-oriented mirrored upper-limb robotic training on the upper-limb functions and activities of daily living of subacute poststroke patients. DESIGN: This study is a single-blinded, active-controlled pilot study. SETTING: The study was carried out at rehabilitation outpatient clinic and ward. POPULATION: A total of 32 subacute poststroke patients were enrolled in the study. METHODS: The enrolled patients were allocated into two groups in a ratio of 1:1. The experimental group received 4 weeks of task-oriented mirrored upper-limb robotic training, consisting of five sessions of 30-minute duration, along with 30 minutes of conventional training. The control group only received 60 minutes of conventional training. The outcome measures were the Fugl-Meyer Assessment Scale for Upper Extremity, Modified Barthel Index, Stroke Self-Efficacy Scale, System Usability Scale, and Quebec User Evaluation with Assistive Technology. RESULTS: All patients completed the full training sessions without significant adverse events related to robotic training. The task-oriented mirrored upper-limb robotic training led to increased Fugl-Meyer Assessment Scale for Upper Extremity (difference: 10.38 points, P<0.001) and Modified Barthel Index (difference: 18.38 points, P<0.001) scores, both of which exceeded the minimal clinically important difference. Intergroup analysis showed significantly higher improvements in the Fugl-Meyer Assessment Scale for Upper Extremity total scores, shoulder, wrist, and hand scores; and Modified Barthel Index scores in the experimental group than in conventional training (all P<0.05). Both groups showed significant improvements in Stroke Self-Efficacy Scale scores after the intervention (both P<0.001), but without a statistically significant intergroup difference (P>0.05). Participants in the experimental group scored an average usability perception score of 74.74 (good) and an average satisfaction score of four or more out of five. CONCLUSIONS: In general, task-oriented mirrored upper-limb robotic training appears feasible and safe for subacute poststroke rehabilitation, facilitating the recovery of upper-limb functions and activities of daily living. CLINICAL REHABILITATION IMPACT: Task-oriented mirrored upper-limb robotic training shows promise for future clinical rehabilitation and clinical trials involving subacute poststroke patients.

Dynamic Repositioning of Aerial Base Stations for Enhanced User Experience in 5G and Beyond.

The ultra-dense deployment (UDD) of small cells in 5G and beyond to enhance capacity and data rate is promising, but since user densities continually change, the static deployment of small cells can lead to wastes of capital, the underutilization of resources, and user dissatisfaction. This work proposes the use of Aerial Base Stations (ABSs) wherein small cells are mounted on Unmanned Aerial Vehicles (UAVs), which can be deployed to a set of candidate locations. Furthermore, based on the current user densities, this work studies the optimal placement of the ABSs, at a subset of potential candidate positions, to maximize the total received power and signal-to-interference ratio. The problems of the optimal placement for increasing received power and signal-to-interference ratio are formulated, and optimal placement solutions are designed. The proposed solutions compute the optimal candidate locations for the ABSs based on the current user densities. When the user densities change significantly, the proposed solutions can be re-executed to re-compute the optimal candidate locations for the ABSs, and hence the ABSs can be moved to their new candidate locations. Simulation results show that a 22% or more increase in the total received power can be achieved through the optimal placement of the Aerial BSs and that more than 60% users have more than 80% chance to have their individual received power increased.

Ultrastrong spinodoid alloys enabled by electrochemical dealloying and refilling.

We present an extreme case of composition-modulated nanomaterial formed by selective etching (dealloying) and electrochemical refilling. The product is a coarse-grain polycrystal consisting of two interwoven nanophases, with identical crystal structures and a cube-on-cube relationship, separated by smoothly curved semicoherent interfaces with high-density misfit dislocations. This material resembles spinodal alloys structurally, but its synthesis and composition modulation are spinodal-independent. Our Cu/Au "spinodoid" alloy demonstrates superior mechanical properties such as near-theoretical strength and single-phase-like behavior, owing to its fine composition modulation, large-scale coherence of crystal lattice, and smoothly shaped three-dimensional (3D) interface morphology. As a unique extension of spinodal alloy, the spinodoid alloy reported here reveals a number of possibilities to modulate the material's structure and composition down to the nanoscale, such that further improved properties unmatchable by conventional materials can be achieved.

A novel necroptosis-related lncRNA signature for predicting prognosis and anti-cancer treatment response in endometrial cancer.

Background: Necroptosis, a form of programmed cell death, underlies tumorigenesis and the progression of cancers. Anti-cancer strategies targeting necroptosis have increasingly been shown to present a potential cancer therapy. However, the predictive utility and anticancer sensitivity value of necroptosis-related lncRNAs (NRLs) for endometrial cancer (EC) are currently unknown. Methods: EC patient gene expression profiles and the corresponding clinical information collected from The Cancer Genome Atlas were used to identify NRLs that constituted a predictive signature for EC. The functional pathways, immune status, clinicopathological correlation, and anticancer drug sensitivity of the patients relative to the NRLs signatures were analyzed. Results: A signature composed of 7 NRLs (AC019080.5, BOLA3-AS1, AC022144.1, AP000345.2, LEF1-AS1, AC010503.4, and RPARP-AS1) was identified. The high-risk patient group with this signature exhibited a poorer prognosis and lower survival rate than low-risk group lacking this signature. This necroptosis-related lncRNA signature had a higher predictive accuracy compared with other clinicopathological variables (area under the receiver operating characteristic curve of the risk score: 0.717). Additionally, when patients were stratified based on other clinicopathological variables, the overall survival was significantly shorter in the high-risk versus low-risk group across all cohorts. Gene set enrichment analysis (GSEA) revealed that immune- and tumor-related signaling pathways and biological processes were enriched in the high-risk group compared to the low-risk group. Single-sample gene set enrichment analysis (ssGSEA) additionally showed that the resulting risk score was strongly correlated with EC patient immune status. Finally, patients with high-risk scores were more sensitive to the anti-cancer drugs such as Docetaxel, Mitomycin.C, Vinblastine, AZD.2281 (olaparib), AZD6244, and PD.0332991 (Palbociclib). Conclusion: These findings reveal a novel necroptosis-related lncRNA signature for predicting EC patient prognosis and shed new light on anticancer therapy strategies for EC.

Low Latency and High Data Rate (LLHD) Scheduler: A Multipath TCP Scheduler for Dynamic and Heterogeneous Networks.

The scheduler is a crucial component of the multipath transmission control protocol (MPTCP) that dictates the path that a data packet takes. Schedulers are in charge of delivering data packets in the right order to prevent delays caused by head-of-line blocking. The modern Internet is a complicated network whose characteristics change in real-time. MPTCP schedulers are supposed to understand the real-time properties of the underlying network, such as latency, path loss, and capacity, in order to make appropriate scheduling decisions. However, the present scheduler does not take into account all of these characteristics together, resulting in lower performance. We present the low latency and high data rate (LLHD) scheduler, which successfully makes scheduling decisions based on real-time information on latency, path loss, and capacity, and achieves around 25% higher throughput and 45% lower data transmission delay than Linux's default MPTCP scheduler.

Performance Evaluation of MPTCP on Simultaneous Use of 5G and 4G Networks.

The 5G cellular network comes with a promise to provide a very high data rate at low latency, which is becoming critical for advancing technologies. Mobile operators are currently deploying the 5G cellular network worldwide. However, because of limited coverage and high susceptibility of the 5G network to obstacles, handoffs from 5G to 4G and vice versa frequently occur, especially when the user equipment (UE) is moving. These handoffs often cause significant delays in data transmission due to packet losses and retransmissions. A promising solution can be to use both 4G and 5G networks simultaneously, which can solve this problem and yield a better throughput. Multipath transmission control protocol (TCP) is an effective solution for this problem, but it requires significant performance evaluation before practical deployment. In this study, we implement an MPTCP testbed based on NS3-DCE that enables to test the performance of MPTCP schedulers and congestion control algorithms (CCAs) in both 3GPP and non-3GPP networks. Through extensive simulation experiments in a scenario where a UE simultaneously utilizes both 4G and 5G networks, we found that blocking estimation (BLEST) scheduler implemented with balanced linked adaptation (BALIA) CCA can produce the highest throughput and lowest delay. Finally, we showed how received signal to interference and noise ratio (SINR), congestion window, throughput, and packet losses are interconnected.

Effects of five teaching methods in clinical nursing teaching: A protocol for systematic review and network meta-analysis.

INTRODUCTION: Several teaching methods have been used in clinical nursing teaching to increase quality and efficiency, but disagreements over their effects persist. This study will evaluate the effects of five teaching methods in clinical nursing on nursing students' knowledge, skill scores, learning satisfaction, and patients' satisfaction. METHODS: We will conduct searches in PubMed, Embase, Web of Science, The Cochrane Library, China National Knowledge Infrastructure Database (CNKI), China Biological literature database (CBM), Wanfang Database, and China Science and Technology Journal Database (CSTJ) up to April 2022. Relevant randomized controlled trials meeting the eligibility criteria will be included. And the study selection and data extraction will be independently screened for eligibility by two authors. The quality of evidence will be evaluated using the Cochrane risk of bias tool. Pairwise meta-analysis and network meta-analysis (NMA) will be conducted using Rev Man, Stata, and R software. Statistical analyses including homogeneity tests, sensitivity analysis, transitivity tests, consistency tests, and publication bias will be completed. ETHICS AND DISSEMINATION: No formal research ethics approval is required. The results will be disseminated to a peer-reviewed journal for publication. PROTOCOL REGISTRATION NUMBER: INPLASY2021120040.

A Review on the Trends in Event Detection by Analyzing Social Media Platforms' Data.

Social media platforms have many users who share their thoughts and use these platforms to organize various events collectively. However, different upsetting incidents have occurred in recent years by taking advantage of social media, raising significant concerns. Therefore, considerable research has been carried out to detect any disturbing event and take appropriate measures. This review paper presents a thorough survey to acquire in-depth knowledge about the current research in this field and provide a guideline for future research. We systematically review 67 articles on event detection by sensing social media data from the last decade. We summarize their event detection techniques, tools, technologies, datasets, performance metrics, etc. The reviewed papers mainly address the detection of events, such as natural disasters, traffic, sports, real-time events, and some others. As these detected events can quickly provide an overview of the overall condition of the society, they can significantly help in scrutinizing events disrupting social security. We found that compatibility with different languages, spelling, and dialects is one of the vital challenges the event detection algorithms face. On the other hand, the event detection algorithms need to be robust to process different media, such as texts, images, videos, and locations. We outline that the event detection techniques compatible with heterogeneous data, language, and the platform are still missing. Moreover, the event and its location with a 24 × 7 real-time detection system will bolster the overall event detection performance.

Maelstrom promotes tumor metastasis through regulation of FGFR4 and epithelial-mesenchymal transition in epithelial ovarian cancer.

BACKGROUND: Increasing evidence has indicated that Maelstrom (MAEL) plays an oncogenic role in various human carcinomas. However, the exact function and mechanisms by which MAEL acts in epithelial ovarian cancer (EOC) remain unclear. RESULTS: This study demonstrated that MAEL was frequently overexpressed in EOC tissues and cell lines. Overexpression of MAEL was positively correlated with the histological grade of tumors, FIGO stage, and pT/pN/pM status (p < 0.05), and it also acted as an independent predictor of poor patient survival (p < 0.001). Ectopic overexpression of MAEL substantially promoted invasiveness/metastasis and induced epithelial-mesenchymal transition (EMT), whereas silencing MAEL by short hairpin RNA effectively inhibited its oncogenic function and attenuated EMT. Further study demonstrated that fibroblast growth factor receptor 4 (FGFR4) was a critical downstream target of MAEL in EOC, and the expression levels of FGFR4 were significantly associated with MAEL. (P < 0.05). CONCLUSION: Our findings suggest that overexpression of MAEL plays a crucial oncogenic role in the development and progression of EOC through the upregulation of FGFR4 and subsequent induction of EMT, and also provide new insights on its potential as a therapeutic target for EOC.

3D Printing of Metal-Organic Framework-Based Ionogels: Wearable Sensors with Colorimetric and Mechanical Responses.

Soft ionotronics are emerging materials as wearable sensors for monitoring physiological signals, sensing environmental hazards, and bridging the human-machine interface. However, the next generation of wearable sensors requires multiple sensing capabilities, mechanical toughness, and 3D printability. In this study, a metal-organic framework (MOF) and three-dimensional (3D) printing were integrated for the synthesis of a tough MOF-based ionogel (MIG) for colorimetric and mechanical sensing. The ink for 3D printing contained deep eutectic solvents (DESs), cellulose nanocrystals (CNCs), MOF crystals, and acrylamide. After printing, further photopolymerization resulted in a second covalently cross-linked poly(acrylamide) network and solidification of MIG. As a porphyrinic Zr-based MOF, MOF-525 served as a functional filler to provide sharp color changes when exposed to acidic compounds. Notably, MOF-525 crystals also provided another design space to tune the printability and mechanical strength of MIG. In addition, the printed MIG exhibited high stability in the air because of the low volatility of DESs. Thereafter, wearable auxetic materials comprising MIG with negative Poisson's ratios were prepared by 3D printing for the detection of mechanical deformation. The resulting auxetic sensor exhibited high sensitivity via the change in resistance upon mechanical deformation and a conformal contact with skins to monitor various human body movements. These results demonstrate a facile strategy for the construction of multifunctional sensors and the shaping of MOF-based composite materials.

mmS-TCP: Scalable TCP for Improving Throughput and Fairness in 5G mmWave Networks.

The millimeter-wave (mmWave) band, which can provide data rates of multi-gigabits per second, could play a major role in achieving the throughput goals of 5G networks. However, the high-bandwidth mmWave signal is susceptible to blockage by various obstacles, which results in very large and frequent degradation in the quality of the received signals. TCP, the most representative transport layer protocol, suffers from significant performance degradation due to the very dynamic channel conditions of the mmWave signal. Therefore, in this paper, we propose a congestion control algorithm that guarantees sufficient throughput in 5G mmWave networks and that does not significantly worsen TCP fairness. The proposed algorithm, which is a modification of Scalable TCP (S-TCP) that is designed for high-speed networks, provides a more stable performance than the existing TCP congestion control algorithm in mmWave networks through simple modifications. In various simulation experiments that considered the actual mobile user environment, the proposed mmWave Scalable TCP (mmS-TCP) algorithm demonstrated throughput up to 2.4 times higher than CUBIC TCP in single flow evaluation, and the inter-protocol fairness index when competing with CUBIC flow significantly improved from 0.819 of S-TCP to 0.9733. Moreover, the mmS-TCP algorithm reduced the number of duplicated ACKs by 1/4 compared with S-TCP, and it improved the average total throughput and intra-protocol fairness simultaneously.

The value of first-trimester platelet parameters in predicting gestational diabetes mellitus.

OBJECTIVE: To explore the potential clinical value of platelet parameters in early pregnancy in predicting gestational diabetes mellitus (GDM). METHODS: A total of 1188 singleton pregnant women were included in the regular antenatal examination and delivered in the First Affiliated Hospital of Sun Yat-Sen University from January 2016 to December 2018, who had no pre-pregnancy diabetes, no factors leading to elevated blood glucose level, no medical complications and no other obstetrical complications. Blood routine examination was performed at the 11-13+6 gestational weeks. All pregnant women underwent 75 g OGTT directly at the 24-28th gestational weeks. And they were divided into GDM group (n = 192) and non-GDM group (n = 996). Binomial Logistic regression analysis and receiver operating characteristic (ROC) curve were used to evaluate the ability of first-trimester platelet parameters to predict GDM, that is the sensitivity and specificity of platelet parameters at the optimal critical value. RESULTS: There were significant differences in platelet count (PLT), platelet distribution width (PDW), mean platelet volume (MPV), and plateletcrit (PCT) between the GDM group and the normal group (p＜.05). After adjusting for the related factors such as maternal age, parity and pregestational body mass index (BMI), the MPV and PCT were correlated with the incidence of GDM (p＜.05). The area under the curve (AUC) of MPV was 0.577; 95% confidence interval (CI) 0.533-0.621 and that of PCT was 0.628. 95%CI 0.582-0.674. PLT and PDW were not correlated with GDM. CONCLUSION: MPV and PCT in early pregnancy are potential indicators in predicting gestational diabetes mellitus.

LECAR: Location Estimation-Based Congestion-Aware Routing Protocol for Sparsely Deployed Energy-Efficient UAVs.

Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time.

BA-MPCUBIC: Bottleneck-Aware Multipath CUBIC for Multipath-TCP.

The Congestion Control Algorithm (CCA) in the Multipath Transmission Control Protocol (MPTCP) is fundamental to controlling the flow of data through multiple subflows (SF) simultaneously. The MPTCP CCA has two design goals: first, always ensure better throughput than single path TCP (SPTCP) flows, and second, collectively, MPTCP SFs going through a shared bottleneck (SB) should occupy bandwidth fairly, i.e., close to the bandwidth occupied by an SPTCP flow. Although several MPTCP CCAs exist, they primarily focus on specific scenarios and could not satisfy the design goals in diverse and dynamic scenarios. Recently, CUBIC has become a widely used CCA for SPTCP for its better compatibility with high-speed internet. CUBIC's effective implementation in the MPTCP is expected to provide improved throughput and fairer behavior, thus satisfying the design goals. However, although the current multipath CUBIC (MPCUBIC) implementation ensures better fairness, it fails to ensure better throughput. We believe the application of same rule for SFs going through an SB and non-shared bottleneck (NSB) makes it difficult for MPCUBIC to adapt to diverse and dynamically changing network scenarios, thus resulting in poor throughput. Therefore, we present an improved version of MPCUBIC, namely bottleneck-aware MPCUBIC (BA-MPCUBIC), to resolve the throughput issue. First, we deploy an innovative bottleneck detection method that successfully differentiates between an SB and NSB based on round-trip-time, enhanced congestion notification, and packet loss. Then, we implement SPTCP CUBIC and MPCUBIC as the CCAs for SFs going through NSBs and SBs, respectively. Extensive emulation experiments demonstrate that the BA-MPCUBIC successfully detects SBs and NSBs with the highest detection accuracy and the lowest detection time compared with other approaches. Moreover, BA-MPCUBIC successfully satisfies the MPTCP design goals in the considered diverse and dynamic scenarios by ensuring both better throughput and fairness.

D-OLIA: A Hybrid MPTCP Congestion Control Algorithm with Network Delay Estimation.

With the recent evolution of mobile technology, modern devices equipped with multiple communication interfaces have become popular. The multipath transmission control protocol (MPTCP) has evolved to facilitate multiple communication interfaces through a single TCP connection for faster Internet access. MPTCP congestion control algorithms (MPTCP-CCAs) control data flow by fulfilling three design goals, i.e., ensuring improvement over single-path flows, ensuring fairness, and balancing congestion. Current MPTCP-CCAs cannot fulfill these design goals. For example, the opportunistic-linked increase algorithm (OLIA), a well-known MPTCP-CCA in load balancing, often results in low throughput because it cannot properly utilize the underlying network. In addition, the current Internet has a rapidly changing characteristic due to a large amount of short-lived traffic, making it difficult for MPTCP-CCAs to cope. An awareness of prevailing network delay conditions might help MPTCP-CCAs to utilize the network capacity fully. Therefore, we propose dynamic OLIA (D-OLIA), a hybrid MPTCP-CCA that enhances the performance of OLIA by integrating an awareness of the current network delay condition for deciding the congestion window (CWND) decrease factor. We estimate the current network delay condition, i.e., less-congested or congested, by observing the changes in the round-trip-time (RTT). Based on the estimated network delay condition, we decide the CWND decrease factor in real-time for reducing the CWND during packet loss events. We implemented D-OLIA in the Linux kernel and experimented using the Mininet emulator. The emulation results demonstrate that D-OLIA successfully estimates current network delay conditions and results in approximately a 20% increased throughput compared to the original OLIA. Compared to certain MPTCP-CCAs, it also yields a highly improved performance in terms of throughput, RTT, packet retransmissions, and fairness among the MPTCP sub-flows.

Light, strong, and stable nanoporous aluminum with native oxide shell.

Aluminum (Al) metal is highly reactive but has excellent corrosion resistance because of the formation of a self-healing passive oxide layer on the surface. Here, we report that this native aluminum oxide shell can also stabilize and strengthen porous Al when the ligament (strut) size is decreased to the submicron or nanometer scale. The nanoporous Al with native oxide shell, which is a nanoporous Al-Al2O3 core-shell composite self-organized in a galvanic replacement reaction, is nonflammable under ambient conditions and stable against coarsening near melting temperatures. This material is stronger than conventional foams of similar density consisting of pure Al or Al-based composites, and also lighter and stronger than most nanoporous metals reported previously. Its light weight, high strength, and excellent stability warrant the explorations of functional and structural applications of this material, if more efficient and scalable synthesis processes are developed in the future.

CHD1L promotes EOC cell invasiveness and metastasis via the regulation of METAP2.

Chromodomain helicase DNA binding protein 1-like (CHD1L) gene has been proposed to play an oncogenic role in human hepatocellular carcinoma. Previously we reported that CHD1L overexpression is significantly associated with the metastasis proceeding of epithelial ovarian cancer (EOC), and may predict a poor prognosis in EOC patients. However, the potential oncogenic mechanisms by which CHD1L acts in EOC remain unclear. To elucidate the oncogenic function of CHD1L, we carried out a series of in vitro assays, with effects of CHD1L ectogenic overexpression and silencing being determined in EOC cell lines (HO8910, A2780 and ES2). Real-time PCR and Western blotting analyses were used to identify potential downstream targets of CHD1L in the process of EOC invasion and metastasis. In ovarian carcinoma HO8910 cell lines, ectopic overexpression of CHD1L substantially induced the invasive and metastasis ability of the cancer cells in vitro. In contrast, knockdown of CHD1L using shRNA inhibited cell invasion in vitro in ovarian carcinoma A2780 and ES2 cell lines. We also demonstrated that methionyl aminopeptidase 2 (METAP2) was a downstream target of CHD1L in EOC, and we found a significant, positive correlation between the expression of CHD1L and METAP2 in EOC tissues (P<0.05). Our findings indicate that CHD1L plays a potential role in the inducement of EOC cancer cell invasion and/or metastasis via the regulation of METAP2 expression and suggests that CHD1L inhibition may provide a potential target for therapeutic intervention in human EOC.

[Clinical characteristics and treatment strategies of prostatic mucinous adenocarcinoma: A report of 10 cases and literature review].

OBJECTIVE: To investigate the clinical characteristics and treatment strategies of prostatic mucinous adenocarcinoma (PMAC). METHODS: We retrospectively analyzed the clinical data on 10 cases of PMAC treated in the First Affiliated Hospital of Nanjing Medical University from January 2014 to June 2018. The patients were aged 51－79 (65 ± 14) years, with a medium PSA level of 89 (14.63－128.05) µg/L and Gleason scores of 3 + 3 in 1 case, 3 + 4 in 2, 4 + 3 in 1 and 8 in 6 cases preoperatively, 1 treated by robot-assisted radical prostatectomy and the other 9 by laparoscopic radical prostatectomy. We conducted pelvic cavity lymph node dissection for all the patients and analyzed their prognosis and survival. RESULTS: Operations were successfully completed in all the cases. Pathological examination revealed 2 cases of mucinous adenocarcinoma with signet ring cell carcinoma in the 10 PMAC patients, 2 at stage ≤T2b, 5 at stage ≥T2c, 3 positive at pelvic lymph node dissection and 5 positive at the incision margin. The patients were followed up for 6－48 (median 26) months. Four of the patients were found with biochemical recurrence within 2 years after operation and treated by androgen-deprivation therapy, radiotherapy and chemotherapy, which reduced the PSA level to <1.0 µg/ml in all the 4 cases. CONCLUSIONS: PMAC has a good prognosis. Radical surgery is recommended for moderate and low-risk PMAC and the patients with postoperative biochemical recurrence can benefit from comprehensive treatment of total androgen blockade.

Overexpression of SLC12A5 is associated with tumor progression and poor survival in ovarian carcinoma.

INTRODUCTION: The solute carrier family 12 member 5 (SLC12A5) gene is playing a putative oncogenic role in colorectal carcinoma. However, the status of SLC12A5 amplification and expression in ovarian carcinoma and its potential clinical and/or prognostic significance has not yet been investigated. METHODS: In the present study, semi-quantitative staining and fluorescence in situ hybridization were used to investigate SLC12A5 protein expression and gene amplification levels. Samples were obtained from archival, formalin-fixed, paraffin-embedded pathological specimens consisting of 30 normal ovaries, 30 ovarian cystadenomas, 30 borderline ovarian tumors, and 147 invasive ovarian carcinomas. SLC12A5 immunohistochemical staining results, pathological parameters, and patient prognosis were then evaluated using various statistical models. Patient survival rate was also assessed using receiver-operator curve analysis. RESULTS: Our results revealed no SLC12A5 protein overexpression in normal ovaries. However, 7% of cystadenomas had SLC12A5 protein overexpression along with 17% of borderline tumors and 37% of ovarian carcinomas (P<0.01). Amplification of SLC12A5 was detected in 10.3% of ovarian carcinomas. Further correlational analyses showed that SLC12A5 protein overexpression in ovarian carcinomas was significantly associated with ascending histological grade, pT/pN/pM status, as well as FIGO stage (P<0.05). A subsequent univariate survival analysis of our ovarian carcinoma cohorts resulted in a significant association between SLC12A5 protein overexpression and decreased patient survival (44.3 and 85.9 months for high and low SLC12A5 protein expression, respectively; P<0.001). Importantly, additional multivariate analysis revealed that SLC12A5 protein expression was a significant, independent prognostic factor for overall survival in ovarian carcinoma patients (P=0.003). CONCLUSIONS: Collectively, these findings support the conclusion that SLC12A5 protein overexpression could indicate an invasive and/or aggressive phenotype of ovarian carcinoma. Future work will need to investigate whether SLC12A5 protein can serve as an independent prognostic molecular marker in patients with ovarian carcinoma.

[Association of polymorphisms in signal transducer and activator of transcription 4 gene and the susceptibility to unexplained recurrent spontaneous abortions].

OBJECTIVE: To investigate the association between the polymorphisms of signal transducer and activator of transcription 4 (STAT4) gene and the susceptibility to unexplained recurrent spontaneous abortion(URSA). METHODS: PCR-restriction fragment length polymorphism (PCR-RFLP) was used to detect genotype 3 loca (rs7574865 G/T, rs10181656 C/G and rs16833431 C/T) polymorphism of STAT4 in 246 URSA cases (URSA group) and 183 normal controls (control group) . RESULTS: (1)The frequencies of rs7574865 were genotype G/G of 36.2% (89/246) in URSA group and 46.4% (85/183) in control group, genotype G/T of 47.2% (116/246) in URSA group and 45.4% (83/183) in control group, and genotype T/T of 16.7% (41/246) in URSA group and 8.2% (15/183) in control group, which reached statistical difference (P < 0.05). The frequencies of rs10181656 were genotype CC of 36.6% (90/246) in URSA group and 46.4% (85/183) in control group, genotype C/G of 48.0% (118/246) in URSA group and 44.8% (82/183) in control group, and genotype G/G of 15.4% (38/246) in URSA group and 8.7% (16/183) in control group, which reached statistical difference (P < 0.05). The carriers of rs7574865 T allele and rs10181656 G allele increased the risk of URSA (OR = 1.51, 1.44, all P < 0.05).(2) There was no different distribution in 3 genotypes (C/C, C/T, T/T) and 2 alleles (C and T) of rs16833431 C/T between URSA patients and normal controls (P = 0.43,0.48). (3) Timated haplotype frequency distribution of rs7574865 G/T and rs10181656 C/G showed haplotype G-T conferring the susceptibility to URSA (OR = 1.49, P < 0.01), but haplotype C-G could provide protection on URSA (OR = 0.68, P < 0.01). CONCLUSION: Polymorphisms of STAT4 gene might confer the susceptibility to URSA by altering STAT4 function and (or) its expression.