Immune landscape and progress in immunotherapy for pituitary neuroendocrine tumors.

Pituitary neuroendocrine tumors (pitNETs) are the second most common primary brain tumors. Despite their prevalence, the tumor immune microenvironment (TIME) and its clinical implications remain largely unexplored. This review provides a comprehensive overview of current knowledge on the immune landscape and advancements in targeted immunotherapy for pitNETs. Macrophages and T cells are principal immune infiltrates within the TIME. Different subtypes of pitNETs display distinct immune patterns, influencing tumor progressive behaviors. PD-L1, the most extensively studied immune checkpoint, is prominently expressed in hormonal pitNETs and correlates with tumor growth and invasion. Cytokines and chemokines including interleukins, CCLs, and CXCLs have complex correlations with tumor subtypes and immune cell infiltration. Crosstalk between macrophages and pitNET cells highlights bidirectional regulatory roles, suggesting potential macrophage-targeted strategies. Recent preclinical studies have demonstrated the efficacy of anti-PD-L1 therapy in a mouse model of corticotroph pitNET. Moreover, anti-PD-1 and/or anti-CTLA-4 immunotherapy has been applied globally in 28 cases of refractory pitNETs, showing more favorable responses in pituitary carcinomas than aggressive pitNETs. In conclusion, the TIME of pitNETs represents a promising avenue for targeted immunotherapy and warrants further investigation.

A machine learning-based integrated clinical model for predicting prognosis in atypical meningioma patients.

PURPOSE: Atypical meningioma (AM) recurs in up to half of patients after surgical resection and may require adjuvant therapy to improve patient prognosis. Various clinicopathological features have been shown to have prognostic implications in AM, but an integrated prediction model is lacking. Thus, in this study, we aimed to develop and validate an integrated prognostic model for AM. METHODS: A retrospective cohort of 528 adult AM patients surgically treated at our institution were randomly assigned to a training or validation group in a 7:3 ratio. Sixteen baseline demographic, clinical, and pathological parameters, progression-free survival (PFS), and overall survival (OS) were analysed. Sixty-five combinations of machine learning (ML) algorithms were used for model training and validation to predict tumour recurrence and patient mortality. RESULTS: The random survival forest (RSF) model was the best model for predicting recurrence and death. Primary or secondary tumour, Ki-67 index, extent of resection, tumour size, brain involvement, tumour necrosis, and age contributed significantly to the model. The C-index value of the RSF recurrence prediction model reached 0.8080. The AUCs for 1-, 3-, and 5-year PFS were 0.83, 0.82, and 0.86, respectively. The C-index value of the RSF death prediction model reached 0.8890. The AUCs for 3-year and 5-year OS were 0.88 and 0.89, respectively. CONCLUSION: A high-performing integrated RSF predictive model for AM recurrence and patient mortality was proposed that may guide therapeutic decision-making and long-term monitoring.

Variability in Donor Lung Culture and Relative Humidity Impact the Stability of 2009 Pandemic H1N1 Influenza Virus on Nonporous Surfaces.

Respiratory viruses can be transmitted by multiple modes, including contaminated surfaces, commonly referred to as fomites. Efficient fomite transmission requires that a virus remain infectious on a given surface material over a wide range of environmental conditions, including different relative humidities. Prior work examining the stability of influenza viruses on surfaces has relied upon virus grown in media or eggs, which does not mimic the composition of virus-containing droplets expelled from the human respiratory tract. In this study, we examined the stability of the 2009 pandemic H1N1 (H1N1pdm09) virus on a variety of nonporous surface materials at four different humidities. Importantly, we used virus grown in primary human bronchial epithelial cell (HBE) cultures from different donors to recapitulate the physiological microenvironment of expelled viruses. We observed rapid inactivation of H1N1pdm09 on copper under all experimental conditions. In contrast to copper, viruses were stable on polystyrene plastic, stainless steel, aluminum, and glass, at multiple relative humidities, but greater decay on acrylonitrile butadiene styrene (ABS) plastic was observed at short time points. However, the half-lives of viruses at 23% relative humidity were similar among noncopper surfaces and ranged from 4.5 to 5.9 h. Assessment of H1N1pdm09 longevity on nonporous surfaces revealed that virus persistence was governed more by differences among HBE culture donors than by surface material. Our findings highlight the potential role of an individual's respiratory fluid on viral persistence and could help explain heterogeneity in transmission dynamics. IMPORTANCE Seasonal epidemics and sporadic pandemics of influenza cause a large public health burden. Although influenza viruses disseminate through the environment in respiratory secretions expelled from infected individuals, they can also be transmitted by contaminated surfaces where virus-laden expulsions can be deposited. Understanding virus stability on surfaces within the indoor environment is critical to assessing influenza transmission risk. We found that influenza virus stability is affected by the host respiratory secretion in which the virus is expelled, the surface material on which the droplet lands, and the ambient relative humidity of the environment. Influenza viruses can remain infectious on many common surfaces for prolonged periods, with half-lives of 4.5 to 5.9 h. These data imply that influenza viruses are persistent in indoor environments in biologically relevant matrices. Decontamination and engineering controls should be used to mitigate influenza virus transmission.

Piperlongumine attenuates angiotensin-II-induced cardiac hypertrophy and fibrosis by inhibiting Akt-FoxO1 signalling.

BACKGROUND: Cardiac hypertrophy and fibrosis are closely related to cardiac dysfunction, especially diastolic dysfunction. Limited medications can be used to simultaneously delay cardiac hypertrophy and fibrosis in clinical practice. Piperlongumine (PLG) is an amide alkaloid extracted from Piper longum and has been shown to have multiple biological effects, including anticancer and antioxidant effects. However, the role of PLG in cardiac hypertrophy and fibrosis is not clear. PURPOSE: The aim of this study was to reveal the role of PLG in cardiac hypertrophy and fibrosis and the associated mechanism. METHODS: Cardiac hypertrophy and fibrosis were induced by angiotensin II (Ang II) in vivo and in vitro. The effect of PLG in vivo, in vitro and its mechanism were investigated by proliferation and apoptosis assays, western blot, real-time PCR, immunofluorescence, histochemistry, echocardiography, flow cytometry and chromatin immunoprecipitation. RESULTS: Proliferation and apoptosis assays showed that 2.5 µM PLG slightly inhibited proliferation and did not promote apoptosis. Treatment with 5 mg/kg PLG obviously inhibited Ang II-induced cardiac hypertrophy and fibrosis in vivo. In vitro studies of neonatal rat cardiomyocytes (NRCMs) showed that the anti-hypertrophic effect of PLG was mediated by reducing the phosphorylation of Akt and thereby preserving the level of Forkhead box transcription factor O1 (FoxO1), since knockdown of FoxO1 by siRNA reversed the protective effect of PLG on NRCMs. In addition, PLG significantly decreased the Ang II-induced expression of profibrotic proteins in neonatal cardiac fibroblasts by reducing the expression of Krüppel-like factor 4 (KLF4) and the recruitment of KLF4 to the promoter regions of transforming growth factor-ß and connective tissue growth factor. CONCLUSION: We demonstrate the cardioprotective effects of PLG in both cardiac hypertrophy and fibrosis and the potential value of PLG for developing novel medications for pathological cardiac hypertrophy and heart failure.

Environmental Persistence of Influenza Viruses Is Dependent upon Virus Type and Host Origin.

Highly transmissible influenza viruses (IV) must remain stable and infectious under a wide range of environmental conditions following release from the respiratory tract into the air. Understanding how expelled IV persist in the environment is critical to limiting the spread of these viruses. Little is known about how the stability of different IV in expelled aerosols is impacted by exposure to environmental stressors, such as relative humidity (RH). Given that not all IV are equally capable of efficient airborne transmission in people, we anticipated that not all IV would respond uniformly to ambient RH. Therefore, we have examined the stability of human-pathogenic seasonal and avian IV in suspended aerosols and stationary droplets under a range of RH conditions. H3N2 and influenza B virus (IBV) isolates are resistant to RH-dependent decay in aerosols in the presence of human airway surface liquid, but we observed strain-dependent variations in the longevities of H1N1, H3N2, and IBV in droplets. Surprisingly, low-pathogenicity avian influenza H6N1 and H9N2 viruses, which cause sporadic infections in humans but are unable to transmit person to person, demonstrated a trend toward increased sensitivity at midrange to high-range RH. Taken together, our observations suggest that the levels of vulnerability to decay at midrange RH differ with virus type and host origin.IMPORTANCE The rapid spread of influenza viruses (IV) from person to person during seasonal epidemics causes acute respiratory infections that can lead to hospitalizations and life-threatening illness. Atmospheric conditions such as relative humidity (RH) can impact the viability of IV released into the air. To understand how different IV are affected by their environment, we compared the levels of stability of human-pathogenic seasonal and avian IV under a range of RH conditions and found that highly transmissible seasonal IV were less sensitive to decay under midrange RH conditions in droplets. We observed that certain RH conditions can support the persistence of infectious viruses on surfaces and in the air for extended periods of time. Together, our findings will facilitate understanding of factors affecting the persistence and spread of IV in our environment.

A Contention-Based Hop-By-Hop Bidirectional Congestion Control Algorithm for Ad-Hoc Networks.

Existing hop-by-hop congestion control algorithms are mainly divided into two categories: those improving the sending rate and those suppressing the receiving rate. However, these congestion control algorithms have problems with validity and limitations. It is likely that the network will be paralyzed due to the unreasonable method of mitigating congestion. In this paper, we present a contention-based hop-by-hop bidirectional congestion control algorithm (HBCC). This algorithm uses the congestion detection method with queue length as a parameter. By detecting the queue length of the current node and the next hop node, the congestion conditions can be divided into the following four categories: 0-0, 0-1, 1-0, 1-1 (0 means no congestion, 1 means congestion). When at least one of the two nodes is congested, the HBCC algorithm adaptively adjusts the contention window of the current node, which can change the priority of the current node to access the channel. In this way, the buffer queue length of the congested node is reduced. When the congestion condition is 1-1, the hop-by-hop priority congestion control (HPCC) method proposed in this paper is used. This algorithm adaptively changes the adjustment degree of the current node competition window and improves the priority of congestion processing of the next hop node. The NS2 simulation shows that by using the HBCC algorithm, when compared with distributed coordination function (DCF) without congestion control, the proposed unidirectional congestion control algorithms hop-by-hop receiving-based congestion control (HRCC) and hop-by-hop sending-based congestion control (HSCC), and the existing congestion control algorithm congestion alleviation-MAC (CA-MAC), the average saturation throughput increased by approximately 90%, 62%, 12%, and 62%, respectively, and the buffer overflow loss ratio reduced by approximately 80%, 79%, 44%, and 79%.

A Virtual Force Algorithm-Lévy-Embedded Grey Wolf Optimization Algorithm for Wireless Sensor Network Coverage Optimization.

The random placement of a large-scale sensor network in an outdoor environment often causes low coverage. In order to effectively improve the coverage of a wireless sensor network in the monitoring area, a coverage optimization algorithm for wireless sensor networks with a Virtual Force-Lévy-embedded Grey Wolf Optimization (VFLGWO) algorithm is proposed. The simulation results show that the VFLGWO algorithm has a better optimization effect on the coverage rate, uniformity, and average moving distance of sensor nodes than a wireless sensor network coverage optimization algorithm using Lévy-embedded Grey Wolf Optimizer, Cuckoo Search algorithm, and Chaotic Particle Swarm Optimization. The VFLGWO algorithm has good adaptability with respect to changes of the number of sensor nodes and the size of the monitoring area.

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

Effect of vasopressin injection technique in laparoscopic excision of bilateral ovarian endometriomas on ovarian reserve: prospective randomized study.

STUDY OBJECTIVE: To evaluate the effects of vasopressin injection technique in laparoscopic cystectomy on ovarian reserve in patients with bilateral endometriomas. DESIGN: Randomized prospective study (Canadian Task Force classification I). SETTING: University hospital. PATIENTS: Eighty-six women with bilateral endometriomas. INTERVENTIONS: Laparoscopic cystectomy of bilateral endometriomas was performed using different techniques including laparoscopic cystectomy by stripping without injection (control group), laparoscopic cystectomy by stripping with injection of saline solution (saline group), and laparoscopic cystectomy by stripping with vasopressin injection technique (VIT group). MEASUREMENTS AND MAIN RESULTS: The number of coagulation events on the ovarian cortex for hemostasis was counted in different groups, and the thickness of ovarian tissues removed was measured. The basal follicle-stimulating hormone (FSH) level was determined before surgery and at 3-, 6-, and 12-month follow-up after laparoscopic cystectomy in the different groups. In the saline group, fewer coagulation events were required to achieve hemostasis, less ovarian tissues were removed, and lower preoperative FSH levels were detected than in the control group (p < .01). In the VIT group, even fewer coagulation events (p < .01) and lower preoperative FSH levels (p < .01) were detected than in the saline group. There was no significant difference in the thickness of ovarian tissues removed in the 2 groups (p > .05). Basal FSH levels were significantly different before and after surgery in the control and saline groups (p < .01) but not in the VIT group (p > .05). CONCLUSION: Vasopressin injection is an ideal procedure to reduce damage from usual laparoscopic cystectomy of bilateral ovarian endometriomas to protect ovarian reserve.

Vascular endothelial growth factor expression up-regulated by endometrial ischemia in secretory phase plays an important role in endometriosis.

Primary human endometrial cells were exposed to hypoxia preconditioning (HPC), HPC-hypoxia, and hypoxia conditions, and then endometrial tissue treated with ischemia preconditioning (IPC) was transplanted onto the chick embryo chorioallantoic membrane to investigate the role of slight ischemia of endometrium in the pathologic process of endometriosis. IPC up-regulated vascular endothelial growth factor expression and decreased apoptosis of endometrial cells, thus facilitating the endometrial fragments' ectopic implantation.